A Cause and Effect Analysis of Motion Trajectories for Modeling Actions

An action is typically composed of different parts of the object moving in particular sequences. The presence of different motions (represented as a 1D histogram) has been used in the traditional bag-of-words (BoW) approach for recognizing actions. However the interactions among the motions also form a crucial part of an action. Different object-parts have varying degrees of interactions with the other parts during an action cycle. It is these interactions we want to quantify in order to bring in additional information about the actions. In this paper we propose a causality based approach for quantifying the interactions to aid action classification. Granger causality is used to compute the cause and effect relationships for pairs of motion trajectories of a video. A 2D histogram descriptor for the video is constructed using these pairwise measures. Our proposed method of obtaining pairwise measures for videos is also applicable for large datasets. We have conducted experiments on challenging action recognition databases such as HMDB51 and UCF50 and shown that our causality descriptor helps in encoding additional information regarding the actions and performs on par with the state-of-the art approaches. Due to the complementary nature, a further increase in performance can be observed by combining our approach with state-of-the-art approaches.

Structure-change-dependent transmittance of PtOx thin film in super-resolution near-field structure: Diffraction effect analysis

To study working mechanism of super-resolution near-field structure (super-RENS) optical disk from a far-field optics view is very necessary because of the actual far-field writing/readout process in the optical disk system. A Gaussian diffraction model based on Fresnel-Kirchhoff diffraction theory of PtOx-type super-RENS has been set up in this Letter. The relationship between micro-structural deformation (change of bubble structure and refractive index profile) with far-field optical response of PtOx thin film has been studied with it in detail. The simulation results are in good agreement with the experimental results reported in literatures with a designed configuration. These results may provide more quantitative information for better understanding of the working mechanism of metal-oxide-type super-RENS. (c) 2007 Elsevier B.V. All rights reserved.

Proposal on How To Conduct a Biopharmaceutical Process Failure Mode and Effect Analysis (FMEA) as a Risk Assessment Tool

With the publication of the quality guideline ICH Q9 "Quality Risk Management" by the International Conference on Harmonization, risk management has already become a standard requirement during the life cycle of a pharmaceutical product. Failure mode and effect analysis (FMEA) is a powerful risk analysis tool that has been used for decades in mechanical and electrical industries. However, the adaptation of the FMEA methodology to biopharmaceutical processes brings about some difficulties. The proposal presented here is intended to serve as a brief but nevertheless comprehensive and detailed guideline on how to conduct a biopharmaceutical process FMEA. It includes a detailed 1-to-10-scale FMEA rating table for occurrence, severity, and detectability of failures that has been especially designed for typical biopharmaceutical processes. The application for such a biopharmaceutical process FMEA is widespread. It can be useful whenever a biopharmaceutical manufacturing process is developed or scaled-up, or when it is transferred to a different manufacturing site. It may also be conducted during substantial optimization of an existing process or the development of a second-generation process. According to their resulting risk ratings, process parameters can be ranked for importance and important variables for process development, characterization, or validation can be identified. LAY ABSTRACT: Health authorities around the world ask pharmaceutical companies to manage risk during development and manufacturing of pharmaceuticals. The so-called failure mode and effect analysis (FMEA) is an established risk analysis tool that has been used for decades in mechanical and electrical industries. However, the adaptation of the FMEA methodology to pharmaceutical processes that use modern biotechnology (biopharmaceutical processes) brings about some difficulties, because those biopharmaceutical processes differ from processes in mechanical and electrical industries. The proposal presented here explains how a biopharmaceutical process FMEA can be conducted. It includes a detailed 1-to-10-scale FMEA rating table for occurrence, severity, and detectability of failures that has been especially designed for typical biopharmaceutical processes. With the help of this guideline, different details of the manufacturing process can be ranked according to their potential risks, and this can help pharmaceutical companies to identify aspects with high potential risks and to react accordingly to improve the safety of medicines.

An automated failure mode and effect analysis based on high-level design specificication with behavior trees

Formal methods have significant benefits for developing safety critical systems, in that they allow for correctness proofs, model checking safety and liveness properties, deadlock checking, etc. However, formal methods do not scale very well and demand specialist skills, when developing real-world systems. For these reasons, development and analysis of large-scale safety critical systems will require effective integration of formal and informal methods. In this paper, we use such an integrative approach to automate Failure Modes and Effects Analysis (FMEA), a widely used system safety analysis technique, using a high-level graphical modelling notation (Behavior Trees) and model checking. We inject component failure modes into the Behavior Trees and translate the resulting Behavior Trees to SAL code. This enables us to model check if the system in the presence of these faults satisfies its safety properties, specified by temporal logic formulas. The benefit of this process is tool support that automates the tedious and error-prone aspects of FMEA.

Incorporating interdependence in risk likelihood analysis to enhance diagnostics in condition monitoring

This research is aimed at addressing problems in the field of asset management relating to risk analysis and decision making based on data from a Supervisory Control and Data Acquisition (SCADA) system. It is apparent that determining risk likelihood in risk analysis is difficult, especially when historical information is unreliable. This relates to a problem in SCADA data analysis because of nested data. A further problem is in providing beneficial information from a SCADA system to a managerial level information system (e.g. Enterprise Resource Planning/ERP). A Hierarchical Model is developed to address the problems. The model is composed of three different Analyses: Hierarchical Analysis, Failure Mode and Effect Analysis, and Interdependence Analysis. The significant contributions from the model include: (a) a new risk analysis model, namely an Interdependence Risk Analysis Model which does not rely on the existence of historical information because it utilises Interdependence Relationships to determine the risk likelihood, (b) improvement of the SCADA data analysis problem by addressing the nested data problem through the Hierarchical Analysis, and (c) presentation of a framework to provide beneficial information from SCADA systems to ERP systems. The case study of a Water Treatment Plant is utilised for model validation.

Analysis of interdigital electro-optic Bragg diffraction grating

Some integrated optics devices can be made based on the interdigital electro-optic Bragg diffraction grating. The point-matching method is extended to the analysis of interdigital electro-optic Bragg diffraction gratings. This method provides a simple and fast analytic expression of the electric field in the structure. The field distributions are used to calculate the optical and electrical characteristic parameters of the gratings. The effects of finite conductor thickness have been taken into account in the analysis. It is shown that the simulation results agree well with the measured data.

Analysis of a temperature sensitive mutation affecting aldehyde oxidase activity in Drosophila melanogaster

A strain of Drosophila melanogaster (mid america stock culture no. hl16) has been reported to be deficient in aldehyde oxidase activity (Hickey and Singh 1982). This strain was characterized during the course of this study and compared to other mutant strains known to be deficient in aldehyde oxidase activity. During the course of this investigation, the hl16 strain was found to be temperature sensitive in its viability. It was found that the two phenotypes, the enzyme deficiency, and the temperature sensitive lethality were the result of two different mutations, both mapping to the X-chromosome. These two mutations were found to be separable by recombination. The enzyme deficiency was found to map to the same locus as the cinnamon mutation, another mutation which affects aldehyde oxidase production. The developmental profile of aldehyde oxidase in the hl16 strain was compared to the developmental profile in the Canton S wild type strain. The aldehyde oxidase activity in adult hl16 individuals was also compared to that of various other strains. It was also found that the aldehyde oxidase activity was temperature sensitive in the adult flies. The temperature sensitive lethality mutation was mapped to position 1-0.1.

Influence of design parameters on linear induction motor end effect

In this paper, a factor referred to as k(f) for linear induction motor end effect analysis is presented. The mathematical model takes into account the longitudinal entry end effect. The entry end effect produces considerable distortion in magnetic field distribution. It is shown how this influence is derived from the machine-developed force that is calculated through the application of the I-D theory. The k(f) factor establishes the relationship between the longitudinal end effect and machine parameters, mainly the number of magnetic poles, secondary resistivity, and frequency.

Analysis of pesticides in food and environmental samples by enzyme-linked immunosorbent assays

Enzyme-linked immunosorbent assays (ELISAs) are the most extensively studied types of immunoassay and their application in pesticide residue monitoring is an area with enormous potential for growth. In comparison with classical analytical methods, ELISA methods offer the possibility of highly sensitive, relatively rapid, and cost-effective measurements. This review introduces the general ELISA formats used, focusing on their use in pesticide analysis. Identifying and studying the effects of interferences in immunoassays is an active area of research and we discuss the matrix effects observed in several studies involving e.g. food, crop and environmental samples. The procedures to eliminate the matrix interferences are briefly discussed. (C) 1998 Elsevier B.V. B.V.

Az ügyfélszerzési mód hatásának vizsgálata a vevőelégedettségre és a lojalitásra a szervezeti piacon (Analyzing the impact of the customer acquisition mode to the customer satisfaction and loyalty on the corporate market – assessing the effect of recommendation with applying structural equation modelling)

A kutatás célja a marketingeszközök hosszú távú hatásának pontosabb megértése szervezetközi viszonylatban a vevőértékelési modellek egyik nehezen számszerűsíthető tényezője, az ajánlás hatásának vizsgálata által. A hatások elemzésére a strukturális egyenlőségek módszerét (Structural Equation Modelling) alkalmazta a szerző. Rámutatott, hogy az ajánlással szerzett ügyfelek elégedettebbek, lojálisabbak és gyakrabban ajánlják a vállalatot a más módon szerzett ügyfeleknél. Az összefüggések feltárása és bizonyítása különösen az ajánlás kumulatív hatása miatt jelentős. Az eredmények gyakorlati alkalmazásával lehetőség nyílik az ügyfélkör differenciáltabb, értékalapú szegmentációjára, amely pontosabb célcsoport-meghatározást lesz lehetővé, és hosszú távon hozzájárul a vállalat optimális ügyfélportfóliójának kialakításához. ______ The research is aimed at more precise understanding of longterm effects of marketing tools in business to business relations by analysing the impacts of recommendation potential, one of the hardly measurable factors of customer value concept. Structural Equation Modelling is applied for conducting effect analysis. The results show that customers acquired with recommendation are more satisfied, more loyal, and make more recommendation that other customer. These results are more interesting if we take the cumulative effect of recommendation in account. They provide bases for a more differentiated segmentation of customers, which results in a more accurate identification of target groups. In the long-run, the application of the customer-value concept considerably contributes to creating an optimal customer portfolio for companies.