Non-disruptive and null-deflection mass flow measurement by a pressure compensation technique

Accurate mass flow measurement is very important in various monitoring and control applications. This paper proposes a novel method of fluid flow measurement by compensating the pressure drop across the ends of measuring unit using a compensating pump. The pressure drop due to the flow is balanced by a feedback control loop. This is a null-deflection type of measurement. As the insertion of such a measuring unit does not affect the functioning of the systems, this is also a non-disruptive flow measurement method. The implementation and design of such a unit are discussed. The system is modeled and simulated using the bond graph technique and it is experimentally validated. (C) 2009 Elsevier Ltd. All rights reserved.

Worst inputs and a bound on the highest peak statistics of a class of non-linear systems

A method is developed by which the input leading to the highest possible response in an interval of time can be determined for a class of non-linear systems. The input, if deterministic, is constrained to have a known finite energy (or norm) in the interval under consideration. In the case of random inputs, the energy is constrained to have a known probability distribution function. The approach has applications when a system has to be put to maximum advantage by getting the largest possible output or when a system has to be designed to the highest maximum response with only the input energy or the energy distribution known. The method is also useful in arriving at a bound on the highest peak distribution of the response, when the excitation is a known random process.As an illustration the Duffing oscillator has been analysed and some numerical results have also been presented.

An approximate analysis of non-linear non-conservative systems subjected to step function excitation

This paper deals with the approximate analysis of the step response of non-linear nonconservative systems by the application of ultraspherical polynomials. From the differential equations for amplitude and phase, set up by the method of variation of parameters, the approximate solutions are obtained by a generalized averaging technique based on ultraspherical polynomial expansions. The Krylov-Bogoliubov results are given by a particular set of these polynomials. The method has been applied to study the step response of a cubic spring mass system in presence of viscous, material, quadratic, and mixed types of damping. The approximate results are compared with the digital and analogue computer solutions and a close agreement has been found between the analytical and the exact results.

Natural modes of a coupled non-linear system

The natural modes of a non-linear system with two degrees of freedom are investigated. The system, which may contain either hard or soft springs, is shown to possess three modes of vibration one of which does not have any counterpart in the linear theory. The stability analysis indicates the existence of seven different modal stability patterns depending on the values of two parameters of non-linearity.

Undamped Cooper pairs in a non-degenerate electron system

Following the reaction matrix technique and the Kanamori approximation. a condition is obtained for the occurence of undamped Cooper pairs in a non-degenerate electron system. Its relevance to induced superconductivity in systems with artificially populated (optically pumped) bands is pointed out.

Studies on non-specific interference due to serum in the avidin-biotin microELISA for monkey chorionic gonadotropin and a method for its elimination

A study has been carried out on the non-specific interference due to serum in the avidin biotin micro-ELISA for monkey chorionic gonadotropin. Results suggest that it is not due to any proteolytic activity in the serum, but immunoglobulin or associated factors interfering at the level of antigen-antibody interaction. This interference was eliminated by heating samples at 60°C for 30 min.

Transfers of Family Businesses to Non-Family Buyers - The Selling Business Family Perspective

This study focuses on business families and how they handle transitions such as business transfers. It also tries to shift the balance of research away from successions and towards business transfers as a key topic for family business researchers. In addition, it contributes to the family business research field by further highlighting the importance of the various different contributions in the family business from business family members other than the entrepreneurial founder. Based on interviews with both business family members and business brokers, it appears as important for business families who are selling their family business that it is managed in a similar way in the future regardless of the shift in ownership and management. It is also important that the employees can stay with the business. However, employees are seldom regarded as potential buyers of the family business; most preferably, from the point of view of business family members, this should be somebody who is similar to themselves. Business transfers can be lengthy processes, but once the family business is sold, previous owners most often want to leave the family business. This disengagement can be difficult for business family members if they have not managed to build up some other identity outside the family business environment. Money may compensate for the loss in the short run, but something else is needed in the long run, since the management of money is usually not perceived as that interesting. A family business transfer can have great influence on the members of the business family who is selling, and therefore it is suggested that personal due diligence could be of some help when planning the transfer. That tool can help business family members to analyse their own personal situation, but it may also make it easier to understand how the other business family members feel about the forthcoming change. Everyone is influenced in different ways during a family business transfer, and awareness of this fact may make it easier for the whole business family to adjust to their new environment.

Enzyme catalysed non-oxidative decarboxylation of aromatic acids II. Identification of active site residues of 2,3-dihydroxybenzoic acid decarboxylase from Aspergillus niger

In order to understand the mechanism of decarboxylation by 2,3-dihydroxybenzoic acid decarboxylase, chemical modification studies were carried out. Specific modification of the amino acid residues with diethylpyrocarbonate, N-bromosuccinimide and N-ethylmaleiimide revealed that at least one residue each of histidine, tryptophan and cysteine were essential for the activity. Various substrate analogs which were potential inhibitors significantly protected the enzyme against inactivation. The modification of residues at low concentration of the reagents and the protection experiments suggested that these amino acid residues might be present at the active site. Studies also suggested that the carboxyl and ortho-hydroxyl groups of the substrate are essential for interaction with the enzyme.

Estimation of signals in colored non gaussian noise based on Gaussian Mixture models

Non-Gaussianity of signals/noise often results in significant performance degradation for systems, which are designed using the Gaussian assumption. So non-Gaussian signals/noise require a different modelling and processing approach. In this paper, we discuss a new Bayesian estimation technique for non-Gaussian signals corrupted by colored non Gaussian noise. The method is based on using zero mean finite Gaussian Mixture Models (GMMs) for signal and noise. The estimation is done using an adaptive non-causal nonlinear filtering technique. The method involves deriving an estimator in terms of the GMM parameters, which are in turn estimated using the EM algorithm. The proposed filter is of finite length and offers computational feasibility. The simulations show that the proposed method gives a significant improvement compared to the linear filter for a wide variety of noise conditions, including impulsive noise. We also claim that the estimation of signal using the correlation with past and future samples leads to reduced mean squared error as compared to signal estimation based on past samples only.

Colours as Non-Verbal Signs on Packages

Colour is an essential aspect of our daily life, and still, it is a neglected issue within marketing research. The main reason for studying colours is to understand the impact of colours on consumer behaviour, and thus, colours should be studied when it comes to branding, advertising, packages, interiors, and the clothes of the employees, for example. This was an exploratory study about the impact of colours on packages. The focus was on low-involvement purchasing, where the consumer puts limited effort into the decision-making. The basis was a scenario in which the consumer faces an unpredictable problem needing immediate action. The consumer may be in hurry, which indicate time pressure. The consumer may lack brand preferences, or the preferred brand may be out of stock. The issue is that the choice is to be made at the point of purchase. Further, the purchasing involves product classes where the core products behind the brands are indistinguishable from each other. Three research questions were posed. Two questions were answered by conjoint analysis, i.e. if colours have an impact on decision-making and if a possible impact is related to the product class. 16 hypothetical packages were designed in two product classes within the healthcare, i.e. painkillers and medicine against sore throats. The last research question aimed at detecting how an analysis could be carried out in order to understand the impact of colours. This question was answered by conducting interviews that were analysed by applying laddering method and a semiotics approach. The study found that colours do indeed have an impact on consumer behaviour, this being related to the context, such as product class. The role of colours on packages was found to be threefold: attention, aesthetics, and communication. The study focused on colours as a means of communication, and it proposes that colours convey product, brand, and product class meanings, these meanings having an impact on consumers’ decision-making at the point of purchase. In addition, the study demonstrates how design elements such as colours can be understood by regarding them as non-verbal signs. The study also presents an empirical design, involving quantitative and qualitative techniques that can be used to gain in depth understanding of the impact of design elements on consumer behaviour. Hannele Kauppinen is associated with CERS, the Centre for Relationship Marketing and Service Management of the Swedish School of Economics and Business Administration

A non-orthogonal distributed space-time coded protocol - Part 1:Signal model and design criteria

In this two-part series of papers, a generalized non-orthogonal amplify and forward (GNAF) protocol which generalizes several known cooperative diversity protocols is proposed. Transmission in the GNAF protocol comprises of two phases - the broadcast phase and the cooperation phase. In the broadcast phase, the source broadcasts its information to the relays as well as the destination. In the cooperation phase, the source and the relays together transmit a space-time code in a distributed fashion. The GNAF protocol relaxes the constraints imposed by the protocol of Jing and Hassibi on the code structure. In Part-I of this paper, a code design criteria is obtained and it is shown that the GNAF protocol is delay efficient and coding gain efficient as well. Moreover GNAF protocol enables the use of sphere decoders at the destination with a non-exponential Maximum likelihood (ML) decoding complexity. In Part-II, several low decoding complexity code constructions are studied and a lower bound on the Diversity-Multiplexing Gain tradeoff of the GNAF protocol is obtained.

Dynamic programming based optimum non-uniform samples for speech reconstruction and coding

Non-uniform sampling of a signal is formulated as an optimization problem which minimizes the reconstruction signal error. Dynamic programming (DP) has been used to solve this problem efficiently for a finite duration signal. Further, the optimum samples are quantized to realize a speech coder. The quantizer and the DP based optimum search for non-uniform samples (DP-NUS) can be combined in a closed-loop manner, which provides distinct advantage over the open-loop formulation. The DP-NUS formulation provides a useful control over the trade-off between bitrate and performance (reconstruction error). It is shown that 5-10 dB SNR improvement is possible using DP-NUS compared to extrema sampling approach. In addition, the close-loop DP-NUS gives a 4-5 dB improvement in reconstruction error.

Non-unitary-weight Space-Time Block Codes with Minimum Decoding Complexity

Space-Time Block Codes (STBCs) from Complex Orthogonal Designs (CODs) are single-symbol decodable/symbol-by-symbol decodable (SSD); however, SSD codes are obtainable from designs that are not CODs. Recently, two such classes of SSD codes have been studied: (i) Coordinate Interleaved Orthogonal Designs (CIODs) and (ii) Minimum-Decoding-Complexity (MDC) STBCs from Quasi-ODs (QODs). The class of CIODs have non-unitary weight matrices when written as a Linear Dispersion Code (LDC) proposed by Hassibi and Hochwald, whereas the other class of SSD codes including CODs have unitary weight matrices. In this paper, we construct a large class of SSD codes with nonunitary weight matrices. Also, we show that the class of CIODs is a special class of our construction.

Scalable non-linear Support Vector Machine using hierarchical clustering

This paper discusses a method for scaling SVM with Gaussian kernel function to handle large data sets by using a selective sampling strategy for the training set. It employs a scalable hierarchical clustering algorithm to construct cluster indexing structures of the training data in the kernel induced feature space. These are then used for selective sampling of the training data for SVM to impart scalability to the training process. Empirical studies made on real world data sets show that the proposed strategy performs well on large data sets.