Global Value Chain Linkages of Manufacturing Export Firms: A Study of The Kannur Home Textile Industry

The literature on the involvement of developing countries in trade has focused on the effects of different aspects of globalization on firms, regions and countries. The study attempts to examine how an export based industry, locallyembedded and originated on the basis of regional strengths has been inserted into the global trade framework. Though the unit of analysis is the manufacturing export firm in the region of Kannur, it represents the entire home textile export industry from the state of Kerala, as close to 90% of fabric exports in home furnishing material, textiles for upholstery and decoration and stitched or fused, and branded made ups are from the region. From a global perspective, how developing countries face newer trade restrictions and overcome non quota barriers by firm and region specific activities within a value chain framework is a major research area, which has already contributions from the Ludhiana woolen cluster (Tewari,1999 ) and the Tirupur cluster in India (Cawthorne, 1995). The study contributes to the value chain literature by examining the governance and upgrading as well as how firms benefit from linkages. India has a number of export oriented agglomerations or regions where firms have been serving export markets for many years. In many cases it is no longer the supply side policy actions that determine how they are able to penetrate new markets or expand existing market share. Based on this study it becomes possible to understand how the global value chain operates in these different industries to examine whether there is a danger of immiserisation of growth or low road growth

Value orientation of professional students in kerala

The present study is on value orientation of professional students•and as such the theoretical value is inherent and implied. Variation on this value is likely to be limited among the subjects. The relevance of the present study is with particular reference, to management as a profession. In organisational settings motivation plays an important role. According to McClelland's theory of needs, achievement, power, and affiliation are the three important needs that help in understanding motivation. Achieve~ent need may be defined as the drive to excel, to achieve in relation to a set of standards, and to strive to succeed. Some people have a compelling drive to succeed. They have a desire to do something better or more efficiently than it has been done before. McClelland found that high achievers differentiate themselves from others by their desire to do things . better. Considering this fact, 'achievement' is included as one of the values for the study

Attribute reduction and missing value imputing with ANN: prediction of learning disabilities

Learning disability (LD) is a neurological condition that affects a child’s brain and impairs his ability to carry out one or many specific tasks. LD affects about 10% of children enrolled in schools. There is no cure for learning disabilities and they are lifelong. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. Just as there are many different types of LDs, there are a variety of tests that may be done to pinpoint the problem The information gained from an evaluation is crucial for finding out how the parents and the school authorities can provide the best possible learning environment for child. This paper proposes a new approach in artificial neural network (ANN) for identifying LD in children at early stages so as to solve the problems faced by them and to get the benefits to the students, their parents and school authorities. In this study, we propose a closest fit algorithm data preprocessing with ANN classification to handle missing attribute values. This algorithm imputes the missing values in the preprocessing stage. Ignoring of missing attribute values is a common trend in all classifying algorithms. But, in this paper, we use an algorithm in a systematic approach for classification, which gives a satisfactory result in the prediction of LD. It acts as a tool for predicting the LD accurately, and good information of the child is made available to the concerned

Impact of Product Quality, Service Quality and Contextual Experience on Customer Perceived Value and Future Buying Intentions

Recognizing that high satisfaction leads to high customer loyalty, companies today are aiming for total customer satisfaction. This article explains relative impact of product quality, service quality and contextual experience on customer perceived value and intention to shop in the future. The data has been collected using a questionnaire from 205 customers of a national retailer chain. The relative importance of product quality, service quality and contextual experience on customer perceived value and thus on customer preference and future intentions was measured using multiple regression. Also, the contribution of perceived value to preference and thus on future buying intention was also measured. Structural Equation Model (SEM) using Amos 4 was used to find the overall fitness of the model. It was found that product quality, service quality and contextual experience have a major influence on customer perceived value

Model Diagnostics in the presence of measurement error

The problem of using information available from one variable X to make inferenceabout another Y is classical in many physical and social sciences. In statistics this isoften done via regression analysis where mean response is used to model the data. Onestipulates the model Y = µ(X) +ɛ. Here µ(X) is the mean response at the predictor variable value X = x, and ɛ = Y - µ(X) is the error. In classical regression analysis, both (X; Y ) are observable and one then proceeds to make inference about the mean response function µ(X). In practice there are numerous examples where X is not available, but a variable Z is observed which provides an estimate of X. As an example, consider the herbicidestudy of Rudemo, et al. [3] in which a nominal measured amount Z of herbicide was applied to a plant but the actual amount absorbed by the plant X is unobservable. As another example, from Wang [5], an epidemiologist studies the severity of a lung disease, Y , among the residents in a city in relation to the amount of certain air pollutants. The amount of the air pollutants Z can be measured at certain observation stations in the city, but the actual exposure of the residents to the pollutants, X, is unobservable and may vary randomly from the Z-values. In both cases X = Z+error: This is the so called Berkson measurement error model.In more classical measurement error model one observes an unbiased estimator W of X and stipulates the relation W = X + error: An example of this model occurs when assessing effect of nutrition X on a disease. Measuring nutrition intake precisely within 24 hours is almost impossible. There are many similar examples in agricultural or medical studies, see e.g., Carroll, Ruppert and Stefanski [1] and Fuller [2], , among others. In this talk we shall address the question of fitting a parametric model to the re-gression function µ(X) in the Berkson measurement error model: Y = µ(X) + ɛ; X = Z + η; where η and ɛ are random errors with E(ɛ) = 0, X and η are d-dimensional, and Z is the observable d-dimensional r.v.

Approximate solutions and error estimates for a Stokes boundary value problem

The aim of this paper is the numerical treatment of a boundary value problem for the system of Stokes' equations. For this we extend the method of approximate approximations to boundary value problems. This method was introduced by V. Maz'ya in 1991 and has been used until now for the approximation of smooth functions defined on the whole space and for the approximation of volume potentials. In the present paper we develop an approximation procedure for the solution of the interior Dirichlet problem for the system of Stokes' equations in two dimensions. The procedure is based on potential theoretical considerations in connection with a boundary integral equations method and consists of three approximation steps as follows. In a first step the unknown source density in the potential representation of the solution is replaced by approximate approximations. In a second step the decay behavior of the generating functions is used to gain a suitable approximation for the potential kernel, and in a third step Nyström's method leads to a linear algebraic system for the approximate source density. For every step a convergence analysis is established and corresponding error estimates are given.

Hyperspectral field measurements to determine dry matter yield and nutritive value of legume-grass swards

Summary: Productivity, botanical composition and forage quality of legume-grass swards are important factors for successful arable farming in both organic and conventional farming systems. As these attributes can vary considerably within a field, a non-destructive method of detection while doing other tasks would facilitate a more targeted management of crops, forage and nutrients in the soil-plant-animal system. This study was undertaken to explore the potential of field spectral measurements for a non destructive prediction of dry matter (DM) yield, legume proportion in the sward, metabolizable energy (ME), ash content, crude protein (CP) and acid detergent fiber (ADF) of legume-grass mixtures. Two experiments were conducted in a greenhouse under controlled conditions which allowed collecting spectral measurements which were free from interferences such as wind, passing clouds and changing angles of solar irradiation. In a second step this initial investigation was evaluated in the field by a two year experiment with the same legume-grass swards. Several techniques for analysis of the hyperspectral data set were examined in this study: four vegetation indices (VIs): simple ratio (SR), normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and red edge position (REP), two-waveband reflectance ratios, modified partial least squares (MPLS) regression and stepwise multiple linear regression (SMLR). The results showed the potential of field spectroscopy and proved its usefulness for the prediction of DM yield, ash content and CP across a wide range of legume proportion and growth stage. In all investigations prediction accuracy of DM yield, ash content and CP could be improved by legume-specific calibrations which included mixtures and pure swards of perennial ryegrass and of the respective legume species. The comparison between the greenhouse and the field experiments showed that the interaction between spectral reflectance and weather conditions as well as incidence angle of light interfered with an accurate determination of DM yield. Further research is hence needed to improve the validity of spectral measurements in the field. Furthermore, the developed models should be tested on varying sites and vegetation periods to enhance the robustness and portability of the models to other environmental conditions.

Patent DE10 2004 037 519 B4 “Sensor Process and Device for Determining a Physical Value“. A Proof of Concept

At present, a fraction of 0.1 - 0.2% of the patients undergoing surgery become aware during the process. The situation is referred to as anesthesia awareness and is obviously very traumatic for the person experiencing it. The reason for its occurrence is mostly an insufficient dosage of the narcotic Propofol combined with the incapability of the technology monitoring the depth of the patient’s anesthetic state to notice the patient becoming aware. A solution can be a highly sensitive and selective real time monitoring device for Propofol based on optical absorption spectroscopy. Its working principle has been postulated by Prof. Dr. habil. H. Hillmer and formulated in DE10 2004 037 519 B4, filed on Aug 30th, 2004. It consists of the exploitation of Intra Cavity Absorption effects in a two mode laser system. In this Dissertation, a two mode external cavity semiconductor laser, which has been developed previously to this work is enhanced and optimized to a functional sensor. Enhancements include the implementation of variable couplers into the system and the implementation of a collimator arrangement into which samples can be introduced. A sample holder and cells are developed and characterized with a focus on compatibility with the measurement approach. Further optimization concerns the overall performance of the system: scattering sources are reduced by re-splicing all fiber-to-fiber connections, parasitic cavities are eliminated by suppressing the Fresnel reflexes of all one fiber ends by means of optical isolators and wavelength stability of the system is improved by the implementation of thermal insulation to the Fiber Bragg Gratings (FBG). The final laser sensor is characterized in detail thermally and optically. Two separate modes are obtained at 1542.0 and 1542.5 nm, tunable in a range of 1nm each. Mode Full Width at Half Maximum (FWHM) is 0.06nm and Signal to Noise Ratio (SNR) is as high as 55 dB. Independent of tuning the two modes of the system can always be equalized in intensity, which is important as the delicacy of the intensity equilibrium is one of the main sensitivity enhancing effects formulated in DE10 2004 037 519 B4. For the proof of concept (POC) measurements the target substance Propofol is diluted in the solvents Acetone and DiChloroMethane (DCM), which have been investigated for compatibility with Propofol beforehand. Eight measurement series (two solvents, two cell lengths and two different mode spacings) are taken, which draw a uniform picture: mode intensity ratio responds linearly to an increase of Propofol in all cases. The slope of the linear response indicates the sensitivity of the system. The eight series are split up into two groups: measurements taken in long cells and measurements taken in short cells.

Value Added by Quality Management

Abstract: Quality Management is an essential part of successful organisations. But the effect of it is mostly not directly visible. The effects are more indirect, and have a time lag till results appear. In today’s challenging times, all activities of an organisation have to proof their ability to add value. While Value Based Management is more focussed on financial value, other concepts and models like EFQM Excellence Model and Kaplan and Norton’s Balanced Score Card also point on values that are the basis and driver for financial success. Quality Management has to proof its effects on company values, and therefore the transacting mechanisms have to be identified and procedure to manage the process of Value Adding Quality Management has to be developed.

Parameter identification of structural dynamic models by inverse statistical analysis

Auf dem Gebiet der Strukturdynamik sind computergestützte Modellvalidierungstechniken inzwischen weit verbreitet. Dabei werden experimentelle Modaldaten, um ein numerisches Modell für weitere Analysen zu korrigieren. Gleichwohl repräsentiert das validierte Modell nur das dynamische Verhalten der getesteten Struktur. In der Realität gibt es wiederum viele Faktoren, die zwangsläufig zu variierenden Ergebnissen von Modaltests führen werden: Sich verändernde Umgebungsbedingungen während eines Tests, leicht unterschiedliche Testaufbauten, ein Test an einer nominell gleichen aber anderen Struktur (z.B. aus der Serienfertigung), etc. Damit eine stochastische Simulation durchgeführt werden kann, muss eine Reihe von Annahmen für die verwendeten Zufallsvariablengetroffen werden. Folglich bedarf es einer inversen Methode, die es ermöglicht ein stochastisches Modell aus experimentellen Modaldaten zu identifizieren. Die Arbeit beschreibt die Entwicklung eines parameter-basierten Ansatzes, um stochastische Simulationsmodelle auf dem Gebiet der Strukturdynamik zu identifizieren. Die entwickelte Methode beruht auf Sensitivitäten erster Ordnung, mit denen Parametermittelwerte und Kovarianzen des numerischen Modells aus stochastischen experimentellen Modaldaten bestimmt werden können.

Alternative plant protein sources for pigs and chickens in the tropics – nutritional value and constraints: a review

In the tropics, a large number of smallholder farms contribute significantly to food security by raising pigs and poultry for domestic consumption and for sale on local markets. The high cost and, sometimes, the lack of availability of commercial protein supplements is one of the main limitations to efficient animal production by smallholders. Locally-grown forages and grain legumes offer ecological benefits such as nitrogen fixation, soil improvement, and erosion control which contribute to improve cropping efficiency. Besides these agronomical assets, they can be used as animal feeds in mixed farming systems. In this paper we review options to include locally-grown forages and grain legumes as alternative protein sources in the diets of pigs and poultry in order to reduce farmers’ dependence on externally-purchased protein concentrates. The potential nutritive value of a wide range of forages and grain legumes is presented and discussed. The influence of dietary fibre and plant secondary metabolites contents and their antinutritive consequences on feed intake, digestive processes and animal performances are considered according to the varying composition in those compounds of the different plant species and cultivars covered in this review. Finally, methods to overcome the antinutritive attributes of the plant secondary metabolites using heat, chemical or biological treatment are reviewed regarding their efficiency and their suitability in low input farming systems.

Molecular Beam Epitaxial Growth of III-V Semiconductor Nanostructures on Silicon Substrates

The main focus and concerns of this PhD thesis is the growth of III-V semiconductor nanostructures (Quantum dots (QDs) and quantum dashes) on silicon substrates using molecular beam epitaxy (MBE) technique. The investigation of influence of the major growth parameters on their basic properties (density, geometry, composition, size etc.) and the systematic characterization of their structural and optical properties are the core of the research work. The monolithic integration of III-V optoelectronic devices with silicon electronic circuits could bring enormous prospect for the existing semiconductor technology. Our challenging approach is to combine the superior passive optical properties of silicon with the superior optical emission properties of III-V material by reducing the amount of III-V materials to the very limit of the active region. Different heteroepitaxial integration approaches have been investigated to overcome the materials issues between III-V and Si. However, this include the self-assembled growth of InAs and InGaAs QDs in silicon and GaAx matrices directly on flat silicon substrate, sitecontrolled growth of (GaAs/In0,15Ga0,85As/GaAs) QDs on pre-patterned Si substrate and the direct growth of GaP on Si using migration enhanced epitaxy (MEE) and MBE growth modes. An efficient ex-situ-buffered HF (BHF) and in-situ surface cleaning sequence based on atomic hydrogen (AH) cleaning at 500 °C combined with thermal oxide desorption within a temperature range of 700-900 °C has been established. The removal of oxide desorption was confirmed by semicircular streaky reflection high energy electron diffraction (RHEED) patterns indicating a 2D smooth surface construction prior to the MBE growth. The evolution of size, density and shape of the QDs are ex-situ characterized by atomic-force microscopy (AFM) and transmission electron microscopy (TEM). The InAs QDs density is strongly increased from 108 to 1011 cm-2 at V/III ratios in the range of 15-35 (beam equivalent pressure values). InAs QD formations are not observed at temperatures of 500 °C and above. Growth experiments on (111) substrates show orientation dependent QD formation behaviour. A significant shape and size transition with elongated InAs quantum dots and dashes has been observed on (111) orientation and at higher Indium-growth rate of 0.3 ML/s. The 2D strain mapping derived from high-resolution TEM of InAs QDs embedded in silicon matrix confirmed semi-coherent and fully relaxed QDs embedded in defectfree silicon matrix. The strain relaxation is released by dislocation loops exclusively localized along the InAs/Si interfaces and partial dislocations with stacking faults inside the InAs clusters. The site controlled growth of GaAs/In0,15Ga0,85As/GaAs nanostructures has been demonstrated for the first time with 1 μm spacing and very low nominal deposition thicknesses, directly on pre-patterned Si without the use of SiO2 mask. Thin planar GaP layer was successfully grown through migration enhanced epitaxy (MEE) to initiate a planar GaP wetting layer at the polar/non-polar interface, which work as a virtual GaP substrate, for the GaP-MBE subsequently growth on the GaP-MEE layer with total thickness of 50 nm. The best root mean square (RMS) roughness value was as good as 1.3 nm. However, these results are highly encouraging for the realization of III-V optical devices on silicon for potential applications.