Blood type classification using computer vision and machine learning

In emergency situations, where time for blood transfusion is reduced, the O negative blood type (the universal donor) is administrated. However, sometimes even the universal donor can cause transfusion reactions that can be fatal to the patient. As commercial systems do not allow fast results and are not suitable for emergency situations, this paper presents the steps considered for the development and validation of a prototype, able to determine blood type compatibilities, even in emergency situations. Thus it is possible, using the developed system, to administer a compatible blood type, since the first blood unit transfused. In order to increase the system’s reliability, this prototype uses different approaches to classify blood types, the first of which is based on Decision Trees and the second one based on support vector machines. The features used to evaluate these classifiers are the standard deviation values, histogram, Histogram of Oriented Gradients and fast Fourier transform, computed on different regions of interest. The main characteristics of the presented prototype are small size, lightweight, easy transportation, ease of use, fast results, high reliability and low cost. These features are perfectly suited for emergency scenarios, where the prototype is expected to be used.

SUPPLIER INVOLVEMENT IN NEW PRODUCT DEVELOPMENT: A CASE STUDY FROM THE SEMICONDUCTOR INDUSTRY

Global competition requires that the companies adapt themselves to technological changes rapidly, develop new products, reduce the cost, shorten the time to market, and increase the quality. In this context, supplier involvement in New Product Development (NPD) is determinant for a company to respond to the requirements of the increasingly dynamic markets. The main purpose of the paper is to demonstrate the importance of supplier involvement in NPD, buyer-supplier relationships and their effects on buyer’s NPD process, highlighting the benefits of supplier involvement, the barriers, the strategic aspects and industry aspects. These issues are addressed with a case study from the semiconductor industry. Besides helping to understand NPD in the semiconductor industry, the contribution and fi ndings of this work are clear: the results achieved confirm the findings of studies referred in the literature review, and confirm that the semiconductor industry sector requires a closer and more complex relationship structure with suppliers, given the specificities and challenges of the sector, such as rapid technological changes, permanent innovation, global competition, reduction of cost and time-to-market cycle, increased capacity, among other. The main contribution of the paper to the scientific literature and to managers is the better understanding of the buyer-supplier relationships in NPD in the semiconductor industry.