Two dynamic discrete choice estimation problems and simulation method solutions

This paper considers two problems that frequently arise in dynamic discrete choice problems but have not received much attention with regard to simulation methods. The first problem is how to simulate unbiased simulators of probabilities conditional on past history. The second is simulating a discrete transition probability model when the underlying dependent variable is really continuous. Both methods work well relative to reasonable alternatives in the application discussed. However, in both cases, for this application, simpler methods also provide reasonably good results.

Social engineering in social networking sites : the art of impersonation

Social networking sites (SNSs), with their large number of users and large information base, seem to be the perfect breeding ground for exploiting the vulnerabilities of people, who are considered the weakest link in security. Deceiving, persuading, or influencing people to provide information or to perform an action that will benefit the attacker is known as “social engineering.” Fraudulent and deceptive people use social engineering traps and tactics through SNSs to trick users into obeying them, accepting threats, and falling victim to various crimes such as phishing, sexual abuse, financial abuse, identity theft, and physical crime. Although organizations, researchers, and practitioners recognize the serious risks of social engineering, there is a severe lack of understanding and control of such threats. This may be partly due to the complexity of human behaviors in approaching, accepting, and failing to recognize social engineering tricks. This research aims to investigate the impact of source characteristics on users’ susceptibility to social engineering victimization in SNSs, particularly Facebook. Using grounded theory method, we develop a model that explains what and how source characteristics influence Facebook users to judge the attacker as credible.

The renormalization group: A perturbation method for the graduate curriculum

In this paper the renormalization group (RG) method of Chen, Goldenfeld, and Oono [Phys. Rev. Lett., 73 (1994), pp.1311-1315; Phys. Rev. E, 54 (1996), pp.376-394] is presented in a pedagogical way to increase its visibility in applied mathematics and to argue favorably for its incorporation into the corresponding graduate curriculum.The method is illustrated by some linear and nonlinear singular perturbation problems. Key word. © 2012 Society for Industrial and Applied Mathematics.

A Combined Renormalization Group-Multiple Scale Method for Singularly Perturbed Problems

This paper introduces a straightforward method to asymptotically solve a variety of initial and boundary value problems for singularly perturbed ordinary differential equations whose solution structure can be anticipated. The approach is simpler than conventional methods, including those based on asymptotic matching or on eliminating secular terms. © 2010 by the Massachusetts Institute of Technology.

Unbalance identification in large steam turbo-generator unit using a model-based method

Fault identification in industrial machine is a topic of major importance under engineering point of view. In fact, the possibility to identify not only the type, but also the severity and the position of a fault occurred along a shaft-line allows quick maintenance and shorten the downtime. This is really important in the power generation industry where the units are often of several tenths of meters long and where the rotors are enclosed by heavy and pressure-sealed casings. In this paper, an industrial experimental case is presented related to the identification of the unbalance on a large size steam turbine of about 1.3 GW, belonging to a nuclear power plant. The case history is analyzed by considering the vibrations measured by the condition monitoring system of the unit. A model-based method in the frequency domain, developed by the authors, is introduced in detail and it is then used to identify the position of the fault and its severity along the shaft-line. The complete model of the unit (rotor – modeled by means of finite elements, bearings – modeled by linearized damping and stiffness coefficients and foundation – modeled by means of pedestals) is analyzed and discussed before being used for the fault identification. The assessment of the actual fault was done by inspection during a scheduled maintenance and excellent correspondence was found with the identified one by means of authors’ proposed method. Finally a complete discussion is presented about the effectiveness of the method, even in presence of a not fine tuned machine model and considering only few measuring planes for the machine vibration.

Application of a hybrid Entropy–McKinsey Matrix method in evaluating sustainable urbanization : a China case study

Although urbanization can promote social and economic development, it can also cause various problems. As the key decision makers of urbanization, local governments should be able to evaluate urbanization performance, summarize experiences, and find problems caused by urbanization. This paper introduces a hybrid Entropy–McKinsey Matrix method for evaluating sustainable urbanization. The McKinsey Matrix is commonly referred to as the GE Matrix. The values of a development index (DI) and coordination index (CI) are calculated by employing the Entropy method and are used as a basis for constructing a GE Matrix. The matrix can assist in assessing sustainable urbanization performance by locating the urbanization state point. A case study of the city of Jinan in China demonstrates the process of using the evaluation method. The case study reveals that the method is an effective tool in helping policy makers understand the performance of urban sustainability and therefore formulate suitable strategies for guiding urbanization toward better sustainability.

Optimizing I/O cost and managing memory for composition vector method based on correlation matrix calculation in bioinformatics

The generation of a correlation matrix for set of genomic sequences is a common requirement in many bioinformatics problems such as phylogenetic analysis. Each sequence may be millions of bases long and there may be thousands of such sequences which we wish to compare, so not all sequences may fit into main memory at the same time. Each sequence needs to be compared with every other sequence, so we will generally need to page some sequences in and out more than once. In order to minimize execution time we need to minimize this I/O. This paper develops an approach for faster and scalable computing of large-size correlation matrices through the maximal exploitation of available memory and reducing the number of I/O operations. The approach is scalable in the sense that the same algorithms can be executed on different computing platforms with different amounts of memory and can be applied to different bioinformatics problems with different correlation matrix sizes. The significant performance improvement of the approach over previous work is demonstrated through benchmark examples.

Synthesis of diketopyrrolopyrrole based copolymers via the direct arylation method for p-channel and ambipolar OFETs

In this paper, we have synthesized two novel diketopyrrolopyrrole (DPP) based donor-acceptor (D-A) copolymers poly{3,6-dithiophene-2-yl-2,5-di(2-octyl)- pyrrolo[3,4-c]pyrrole-1,4-dione-alt-1,5-bis(dodecyloxy)naphthalene} (PDPPT-NAP) and poly{3,6-dithiophene-2-yl-2,5-di(2-butyldecyl)-pyrrolo[3,4-c]pyrrole-1,4- dione-alt-2-dodecyl-2H-benzo[d][1,2,3]triazole} (PDPPT-BTRZ) via direct arylation organometallic coupling. Both copolymers contain a common electron withdrawing DPP building block which is combined with electron donating alkoxy naphthalene and electron withdrawing alkyl-triazole comonomers. The number average molecular weight (Mn) determined by gel permeation chromatography (GPC) for polymer PDPPT-NAP is around 23 400 g mol-1 whereas for polymer PDPPT-BTRZ it is 18 600 g mol-1. The solid state absorption spectra of these copolymers show a wide range of absorption from 400 nm to 1000 nm with optical band gaps calculated from absorption cut off values in the range of 1.45-1.30 eV. The HOMO values determined for PDPPT-NAP and PDPPT-BTRZ copolymers from photoelectron spectroscopy in air (PESA) data are 5.15 eV and 5.25 eV respectively. These polymers exhibit promising p-channel and ambipolar behaviour when used as an active layer in organic thin-film transistor (OTFT) devices. The highest hole mobility measured for polymer PDPPT-NAP is around 0.0046 cm2 V-1 s-1 whereas the best ambipolar performance was calculated for PDPPT-BTRZ with a hole and electron mobility of 0.01 cm2 V-1 s-1 and 0.006 cm2 V-1 s-1.

A new method of interfacing battery/supercapacitor energy storage systems for distributed energy sources

Battery-supercapacitor hybrid energy storage systems can achieve better power and energy performances compared to their individual use. These hybrid systems require separate dc-dc converters, or at least one dc-dc converter for the supercapacitor bank, to connect them to the dc-link of the grid connecting inverter. However, the use of such dc-dc converters introduces additional cost and power losses. Therefore, the possibility of direct connection of energy storage systems, to the dc-link of a diode clamped 3-level inverter is investigated in this paper. Even though the proposed topology does not use dc-dc converters, a vector selection method is proposed to produce a similar control flexibility that is found in the separate dc-dc converter topology. The major issue with the proposed system is the imminent imbalance of the neutral point potential. A PWM technique with modified carriers is used to solve this problem. Simulations are carried out using MATLAB/SIMULINK to verify the efficacy of the proposed system.

A novel dc-link voltage regulation method for single source hybrid multilevel inverters

This paper presents a novel dc-link voltage regulation technique for a hybrid inverter system formed by cascading two 3-level inverters. The two inverters are named as “bulk inverter” and “conditioning inverter”. For the hybrid system to act as a nine level inverter, conditioning inverter dc link voltage should be maintained at one third of the bulk inverter dc link voltage. Since the conditioning inverter is energized by two series connected capacitors, dc-link voltage regulation should be carried out by controlling the capacitor charging/discharging times. A detailed analysis of conditioning inverter capacitor charging/discharging process and a simplified general rule, derived from the analysis, are presented in this paper. Time domain simulations were carried out to demonstrate efficacy of the proposed method on regulating the conditioning inverter dc-link voltage under various operating conditions.

A review selection method using product feature taxonomy

As of today, online reviews have become more and more important in decision making process. In recent years, the problem of identifying useful reviews for users has attracted significant attentions. For instance, in order to select reviews that focus on a particular feature, researchers proposed a method which extracts all associated words of this feature as the relevant information to evaluate and find appropriate reviews. However, the extraction of associated words is not that accurate due to the noise in free review text, and this affects the overall performance negatively. In this paper, we propose a method to select reviews according to a given feature by using a review model generated based upon a domain ontology called product feature taxonomy. The proposed review model provides relevant information about the hierarchical relationships of the features in the review which captures the review characteristics accurately. Our experiment results based on real world review dataset show that our approach is able to improve the review selection performance according to the given criteria effectively.

A novel method of Fiber Bragg Grating (FBG) strain modulation and its application in FBG accelerometers

This thesis has systemically investigated the possibility of improving one type of optical fiber sensors by using a novel mechanism. Many parameters of the sensor have been improved, and one outcome of this innovation is that civil structures, such as bridges and high-rise buildings, may be operated more safely and used longer.

A rating aggregation method for generating product reputations

Many websites offer the opportunity for customers to rate items and then use customers' ratings to generate items reputation, which can be used later by other users for decision making purposes. The aggregated value of the ratings per item represents the reputation of this item. The accuracy of the reputation scores is important as it is used to rank items. Most of the aggregation methods didn't consider the frequency of distinct ratings and they didn't test how accurate their reputation scores over different datasets with different sparsity. In this work we propose a new aggregation method which can be described as a weighted average, where weights are generated using the normal distribution. The evaluation result shows that the proposed method outperforms state-of-the-art methods over different sparsity datasets.