Management and Technology Life Cycle: Bulgarian Case Study on the Technology of Counter-pressure Casting

At IIASA, several researchers have studied and described the cumulative nature of development of technologies and their substitution, using global and macro-economic data. Those processes have their "fine micro-structure" which is interesting and valuable for one country as a whole or for individual companies. Studying this micro-structure can permit us to connect global theory with processes taking place on the micro-level and, based on that, to make recommendations to decision-makers to permit them to select instruments for analyzing and synthesizing their strategy. Small countries often have limited resources (either natural or financial or even both). However, they always have limited human resources which should be used effectively and purposefully. Today, technological developments even outside the sphere of so-called high-tech are very intensive scientifically and intellectually. This once more increases the necessity for small countries to concentrate their scientific human potential in areas in which they can make break-throughs with high economic efficiency. From this point, positioning technological innovations correctly in the international market and forecasting their competitiveness are very important. A picture of the possible future development of a technological innovation gives the small countries and their companies the opportunity to spot market niches and to develop effective strategies for their fulfillment. The application of life cycle theory and use of substitution curves as possible management instruments for strategy development on company level is one of the main goals of the research currently being carried out in Bulgaria under the contract with IIASA's "Management of the Technological Life Cycle" (MTL) activity, part of the "Technology-Economy-Society" (TES) program. The research in Bulgaria is being conducted by the Problem Center "Management of Technological Development" through the Institute for Social Management and has broader goals in the area. These goals are directed towards enhancing instruments for strategic management on company level and methods for accelerating technological development. The Bulgarian study is directed to three main groups of technologies (irrespective of branch of industry): a) original Bulgarian technologies with possibilities on international market; b) new technologies transferred from other countries; and c) traditional mature technologies. Structuring the research in this way not only avoids certain drawbacks inherent in research based on particular characteristics of industrial branches (namely the questionable validity of results and lack of transferability of those results to other branches of industry). It also permits researchers to study the dynamics of these technologies and the dynamics of organizational and management characteristics of the companies independent of branch specification, according to the type of technology described and the degree of its development. In the paper presented, some results of the first stage of the study are discussed. The objects of this first stage are several original Bulgarian technologies. The case study presented here concerns the technology of counter-pressure casting. This original Bulgarian technology is part of a group of technologies based on the method of casting with counter-pressure developed by the Bulgarian Academy of Sciences. The company under study is an interesting integration of a basic research institute, with applied research and production functions. Preliminary results based only on aluminum casting technology are presented in this paper. This method is also being applied to plastic and steel casting technologies which will be addressed in the second stage of the study. Variables and indicators through which technology is studied are developed within the MTL activity, but for the purposes of national study have been adapted, increased in number, and developed according to the specific requirements of a centrally planned economy by the Bulgarian national team

FOOD QUALITY EVALUATION ACCORDING TO THEIR COLOR CHARACTERISTICS

This paper looks at some of the most important aspects related to sensory characteristics and examples of applications of color characteristics to define the quality of food products. The purpose of the study is exploring the possibilities of combining data from different sensors in order to increase the accuracy of classification of food products. For the assessment of quality there is used probabilistic neural networks. The procedure has been successfully tested to increase the accuracy in data experiments for quality classification citrus juices. The results show the potential of the proposed type of classifiers to be used as a rapid, objective and non-destructive tool for quality assessment on real recognition systems in the near future

INTELLIGENT CLASSIFIERS FOR NON-DESTRUCTIVE DETERMINATION OF FOOD QUALITY

The paper analyzes the possibilities to non-destructively determine food quality (potatoes, eggs) by means of the spectra of transmission in the visible and near-infrared regions of the electromagnetic spectrum. The research includes the creation and testing of a training sample of representative samples and the evaluation of the possibilities for classification using Neural Classifier and Support Vector Machines method (SVM).Key words: non-destructive quality evaluation, pattern recognition, food quality, classifier

Representational ethical model calibration

Equity is widely held to be fundamental to the ethics of healthcare. In the context of clinical decision-making, it rests on the comparative fidelity of the intelligence – evidence-based or intuitive – guiding the management of each individual patient. Though brought to recent attention by the individuating power of contemporary machine learning, such epistemic equity arises in the context of any decision guidance, whether traditional or innovative. Yet no general framework for its quantification, let alone assurance, currently exists. Here we formulate epistemic equity in terms of model fidelity evaluated over learnt multidimensional representations of identity crafted to maximise the captured diversity of the population, introducing a comprehensive framework for Representational Ethical Model Calibration. We demonstrate the use of the framework on large-scale multimodal data from UK Biobank to derive diverse representations of the population, quantify model performance, and institute responsive remediation. We offer our approach as a principled solution to quantifying and assuring epistemic equity in healthcare, with applications across the research, clinical, and regulatory domains

NiftyNet: a deep-learning platform for medical imaging

Medical image analysis and computer-assisted intervention problems are increasingly being addressed with deep-learning-based solutions. Established deep-learning platforms are flexible but do not provide specific functionality for medical image analysis and adapting them for this application requires substantial implementation effort. Thus, there has been substantial duplication of effort and incompatible infrastructure developed across many research groups. This work presents the open-source NiftyNet platform for deep learning in medical imaging. The ambition of NiftyNet is to accelerate and simplify the development of these solutions, and to provide a common mechanism for disseminating research outputs for the community to use, adapt and build upon. NiftyNet provides a modular deep-learning pipeline for a range of medical imaging applications including segmentation, regression, image generation and representation learning applications. Components of the NiftyNet pipeline including data loading, data augmentation, network architectures, loss functions and evaluation metrics are tailored to, and take advantage of, the idiosyncracies of medical image analysis and computer-assisted intervention. NiftyNet is built on TensorFlow and supports TensorBoard visualization of 2D and 3D images and computational graphs by default. We present 3 illustrative medical image analysis applications built using NiftyNet: (1) segmentation of multiple abdominal organs from computed tomography; (2) image regression to predict computed tomography attenuation maps from brain magnetic resonance images; and (3) generation of simulated ultrasound images for specified anatomical poses. NiftyNet enables researchers to rapidly develop and distribute deep learning solutions for segmentation, regression, image generation and representation learning applications, or extend the platform to new applications.Comment: Wenqi Li and Eli Gibson contributed equally to this work. M. Jorge Cardoso and Tom Vercauteren contributed equally to this work. 26 pages, 6 figures; Update includes additional applications, updated author list and formatting for journal submissio

Interband mixing between two-dimensional states localized in a surface quantum well and heavy hole states of the valence band in narrow gap semiconductor

Theoretical calculations in the framework of Kane model have been carried out in order to elucidate the role of interband mixing in forming the energy spectrum of two-dimensional carriers, localized in a surface quantum well in narrow gap semiconductor. Of interest was the mixing between the 2D states and heavy hole states in the volume of semiconductor. It has been shown that the interband mixing results in two effects: the broadening of 2D energy levels and their shift, which are mostly pronounced for semiconductors with high doping level. The interband mixing has been found to influence mostly the effective mass of 2D carriers for large their concentration, whereas it slightly changes the subband distribution in a wide concentration range.Comment: 12 pages (RevTEX) and 4 PostScript-figure

Tunnelling Studies of Two-Dimensional States in Semiconductors with Inverted Band Structure: Spin-orbit Splitting, Resonant Broadening

The results of tunnelling studies of the energy spectrum of two-dimensional (2D) states in a surface quantum well in a semiconductor with inverted band structure are presented. The energy dependence of quasimomentum of the 2D states over a wide energy range is obtained from the analysis of tunnelling conductivity oscillations in a quantizing magnetic field. The spin-orbit splitting of the energy spectrum of 2D states, due to inversion asymmetry of the surface quantum well, and the broadening of 2D states at the energies, when they are in resonance with the heavy hole valence band, are investigated in structures with different strength of the surface quantum well. A quantitative analysis is carried out within the framework of the Kane model of the energy spectrum. The theoretical results are in good agreement with the tunnelling spectroscopy data.Comment: 29 pages, RevTeX, submitted in Phys.Rev.B. Figures available on request from [email protected]

Is It Rational to Assume that Infants Imitate Rationally? A Theoretical Analysis and Critique

It has been suggested that preverbal infants evaluate the efficiency of others' actions (by applying a principle of rational action) and that they imitate others' actions rationally. The present contribution presents a conceptual analysis of the claim that preverbal infants imitate rationally. It shows that this ability rests on at least three assumptions: that infants are able to perceive others' action capabilities, that infants reason about and conceptually represent their own bodies, and that infants are able to think counterfactually. It is argued that none of these three abilities is in place during infancy. Furthermore, it is shown that the idea of a principle of rational action suffers from two fallacies. As a consequence, is it suggested that it is not rational to assume that infants imitate rationally. Copyright (C) 2012 S. Karger AG, Base

Genetic and neurological foundations of customer orientation: field and experimental evidence

We explore genetic and neurological bases for customer orientation (CO) and contrast them with sales orientation (SO). Study 1 is a field study that establishes that CO, but not SO, leads to greater opportunity recognition. Study 2 examines genetic bases for CO and finds that salespeople with CO are more likely to have the 7R variant of the DRD4 gene. This is consistent with basic research on dopamine receptor activity in the brain that underlies novelty seeking, the reward function, and risk taking. Study 3 examines the neural basis of CO and finds that salespeople with CO, but not SO, experience greater activation of their mirror neuron systems and neural processes associated with empathy. Managerial and research implications are discussed