On-line Certification for All: The PINVOX Algorithm

A protoype algorithm: PINVOX ("Personal Identification Number by Voice") for on-line certification is introduced to guarantee that scholars have followed, i.e., listened and watched, a complete recorded lecture with the option of earning a certificate or diploma of completion after remotely attending courses. It is based on the injection of unique, randomly selected and pre-recorded integer numbers (or single letters or words) within the audio trace of a video stream at places where silence is automatically detected. The certificate of completion or "virtual attendance" is generated on-the-fly after the successful identification of the embedded PINVOX code by a video viewer student

A Sequential Quadratic Programming Method for Volatility Estimation in Option Pricing

Our goal is to identify the volatility function in Dupire's equation from given option prices. Following an optimal control approach in a Lagrangian framework, we propose a globalized sequential quadratic programming (SQP) algorithm with a modified Hessian - to ensure that every SQP step is a descent direction - and implement a line search strategy. In each level of the SQP method a linear-quadratic optimal control problem with box constraints is solved by a primal-dual active set strategy. This guarantees L1 constraints for the volatility, in particular assuring its positivity. The proposed algorithm is founded on a thorough first- and second-order optimality analysis. We prove the existence of local optimal solutions and of a Lagrange multiplier associated with the inequality constraints. Furthermore, we prove a sufficient second-order optimality condition and present some numerical results underlining the good properties of the numerical scheme.Dupire equation, parameter identification, optimal control, optimality conditions, SQP method, primal-dual active set strategy

Support vector machines in hyperspectral imaging spectroscopy with application to material identification

A processing methodology based on Support Vector Machines is presented in this paper for the classification of hyperspectral spectroscopic images. The accurate classification of the images is used to perform on-line material identification in industrial environments. Each hyperspectral image consists of the diffuse reflectance of the material under study along all the points of a line of vision. These images are measured through the employment of two imaging spectrographs operating at Vis-NIR, from 400 to 1000 nm, and NIR, from 1000 to 2400 nm, ranges of the spectrum, respectively. The aim of this work is to demonstrate the robustness of Support Vector Machines to recognise certain spectral features of the target. Furthermore, research has been made to find the adequate SVM configuration for this hyperspectral application. In this way, anomaly detection and material identification can be efficiently performed. A classifier with a combination of a Gaussian Kernel and a non linear Principal Component Analysis, namely k-PCA is concluded as the best option in this particular case. Finally, experimental tests have been carried out with materials typical of the tobacco industry (tobacco leaves mixed with unwanted spurious materials, such as leathers, plastics, etc.) to demonstrate the suitability of the proposed technique

Significance of Supplier Selection Criteria Evolvement in IT Outsourcing to Emerging Economies - Lessons from a Global IT Outsourcing Project

In line with the increasing significance of the acceleration of information technology (IT) advancement and also of harnessing the vigor of emerging economies, IT outsourcing to emerging economies has become global concerns. This enables global companies to enjoy a critical competitive edge by choosing the best option in outsourcing strategy and supplier selection. Consequently, supplier selection criteria have become critical issues for both suppliers and customers. This paper attempts to provide insightful suggestions to these issues. An empirical analysis was conducted taking supplier selection criteria evolvement in global IT outsourcing project focusing on action research in a multinational company. Noteworthy findings include impacts of manager’s change, identification of creative moment and weighting of supplier selection criteria

Tax Evasion Dynamics in Romania Reflected by Fiscal Inspection Activities

The paper aims to provide a panoramic view of the dynamics of tax evasion in Romania, reflected in terms of fiscal inspection activities. The author used the official data published by the institutions with attributions on the line of identification and fighting against tax evasion (National Agency of Fiscal Administration and Financial Guard) with the view to reflect the real situation concerning the number of inspections, quantify and sanction tax evasion for 2003-2008 periods. Although the number of fiscal inspections and the number of tax payers who have violated the rules of fiscal discipline decreased compared with 2003, the frequency of tax evasion remained. At the same time, based on the data referring to the level and dynamics of the tax dodger phenomenon appreciations have been made regarding the fiscal discipline of the Romanian tax payer and to the attitude of the qualified institutions in discovering and sanctioning the fraudulent tax evasion. In this respect, the author observed that the level of willingness of tax legislation in relation to the Romanian tax payer has not changed considerably.The level of identified tax evasion reported to real GDP increased slightly. This situation can be interpreted as a success of institutions in charge of identification and fighting of tax evasion, a result of the increase of fiscal inspection number and detection probability, but also a result of GDP growth at a rate lower than the identified tax evasion. The author has also tried to find a causality relation between the option for tax evasion and corruption. The author found that a corrupt environment facilitates the decision to evade depending on detection probability, penalty system and bribery level as discouraging factors for tax evasion. The level of identified tax evasion is smaller than the real level of entire tax evasion, an important part being impossible to determine because of corruption.tax evasion, fiscal fraud, fiscal inspections, fiscal discipline,voluntary fiscal compliance, underground economy, corruption

Cross-codex Learning for Reliable Scribe Identification in Medieval Manuscripts

Historic scribe identification is a substantial task for obtaining information about the past. Uniform script styles, such as the Carolingian minuscule, make it a difficult task for classification to focus on meaningful features. Therefore, we demonstrate in this paper the importance of cross-codex training data for CNN based text-independent off-line scribe identification, to overcome codex dependent overfitting. We report three main findings: First, we found that preprocessing with masked grayscale images instead of RGB images clearly increased the F1-score of the classification results. Second, we trained different neural networks on our complex data, validating time and accuracy differences in order to define the most reliable network architecture. With AlexNet, the network with the best trade-off between F1-score and time, we achieved for individual classes F1-scores of up to 0,96 on line level and up to 1.0 on page level in classification. Third, we could replicate the finding that the CNN output can be further improved by implementing a reject option, giving more stable results. We present the results on our large scale open source dataset -- the Codex Claustroneoburgensis database (CCl-DB) -- containing a significant number of writings from different scribes in several codices. We demonstrate for the first time on a dataset with such a variety of codices that paleographic decisions can be reproduced automatically and precisely with CNNs. This gives manifold new and fast possibilities for paleographers to gain insights into unlabeled material, but also to develop further hypotheses

Differentiating signals to make biological sense – a guide through databases for MS-based non-targeted metabolomics

Metabolite identification is one of the most challenging steps in metabolomics studies and reflects one of the greatest bottlenecks in the entire workflow. The success of this step determines the success of the entire research, therefore the quality at which annotations are given requires special attention. A variety of tools and resources are available to aid metabolite identification or annotation, offering different and often complementary functionalities. In preparation for this article, almost 50 databases were reviewed, from which 17 were selected for discussion, chosen for their on-line ESI-MS functionality. The general characteristics and functions of each database is discussed in turn, considering the advantages and limitations of each along with recommendations for optimal use of each tool, as derived from experiences encountered at the Centre for Metabolomics and Bioanalysis (CEMBIO) in Madrid. These databases were evaluated considering their utility in non-targeted metabolomics, including aspects such as ID assignment, structural assignment and interpretation of results

Fidaxomicin is a Superior Treatment to Vancomycin for Recurrent Clostridium Difficile Infection

Clostridium difficile has been historically viewed as a hospital acquired infection. However, the emergence of community acquired infection in low risk populations, the identification of new risk factors, detection of a hypervirulent strain of C. difficile, and increasing mortality have changed the epidemiology if this infection. Current standards of treatment have come into question due to increasing recurrence rates and treatment failures, possible resistance of Metronidazole, and concerns surrounding Vancomycin resistant enterococci (VRE). Fidaxomicin, a narrow-spectrum macrolide, is the first drug approved by the FDA in 20 years for the treatment of C. difficile infection. It has shown good in vitro and in vivo activity, has similar clinical cure rates, lower recurrence rates, and higher global cure rates compared to Vancomycin in non-hypervirulent strains and similar efficacy in all outcomes in the hypervirulent strain. Overall, Fidaxomicin appears to be a reasonable second line treatment option for recurrent C. difficile infection in patients who have failed to respond to treatment under the current guidelines

The Role of Interferon in Hepatitis B Therapy

Despite the introduction of new nucleos(t)ide analogues in recent years, peginterferon is still recommended as a potential first-line treatment option by current practice guidelines for the management of chronic hepatitis B. Peginterferon offers the advantage of higher sustained off-treatment response rates compared to nucleos(t)ide analogues because of its immunomodulatory effects. Sustained transition to the inactive hepatitis B surface antigen (HBsAg) carrier state can be achieved in about 30% of hepatitis B e antigen (HBeAg)–positive patients and 20% of HBeAg-negative patients. Recent studies have focused on identification of pretreatment and on-treatment factors that allow the selection of patients who are likely to achieve a sustained response to peginterferon therapy in order to avoid the side-effects and costs associated with unnecessary treatment. Future studies need to address whether specific virologic benchmarks can guide individualized decisions concerning therapy continuation and whether peginterferon combined with new potent nucleos(t)ide analogues improves treatment outcomes