Within highly competitive business environments, data mining (DM) is viewed as a significant technology to enhance decision-making processes by transforming data into valuable and actionable information to gain competitive advantage. There appears, however, to be a dearth of empirical case studies which consider in detail the initial stages in DM management to enable apt foundation for its later successful implementation. Our research applied a multi-method strategy to determine the critical success factors of embryonic DM implementation. We propose and validate, through a series of cases, a conceptual framework to guide practitioners’ adoption of DM.
COBISS.SI-ID: 28277799
An exploratory study of impact of housing on the characteristics of a Low-Temperature Co-fired Ceramic (LTCC) pressure sensor is presented. The ceramic sensor structure is sealed in a plastic housing. This may have a not negligible effect on the final characteristics and should be considered in the early design phase. The manufacturability issue mainly concerning the selection of available housings and the most appropriate materials were considered in respect of different requirements for low and high pressure range of operation. Numerical predictions showed the trends and helped revealing the critical design parameters. Proper selection of the adhesive material remains essential issue. Curing of the epoxy adhesive may introduce non-negligible residual stresses, which considerably influence the sensor’s characteristics.
COBISS.SI-ID: 29179175
The System Usability Scale (SUS) is a widely adopted and studied questionnaire for usability evaluation. It is technology independent and has been used to evaluate the perceived usability of a broad range of products, including hardware, software, and websites. In this paper we present a Slovene translation of the SUS (the SUS-SI) along with the procedure used in its translation and psychometric evaluation. The results indicated that the SUS-SI has properties similar to the English version. Slovene usability practitioners should be able to use the SUS-SI with confidence when conducting user research.
COBISS.SI-ID: 28316455
The design optimization of an axial flux permanent magnet synchronous machine with a coreless stator and double external rotor is accomplished by using evolutionary optimization with a genetic algorithm and an analytical evaluation of objective functions. On the basis of eight variable geometry parameters, five objective functions are optimized in order to determine the maximum volume torque density and weight torque density, the minimum volume and weight of permanent magnets per Newton-meter, and the minimum machine price per Newton-meter. Based on the geometric parameters for minimum machine price per Newton-meter, a prototype is built for the rated torque. Optimized and analytically evaluated machine characteristics are validated with a finite-element method (FEM) and the measurements of a prototype. Evolutionary optimization with the analytical evaluation of objective functions significantly shortens the computational time required for design optimization in comparison with the FEM.
COBISS.SI-ID: 84086785
We propose a holistic approach to the problem of re-identification in an environment of distributed smart cameras. We model the re-identification process in a distributed camera network as a distributed multi-class classifier, composed of spatially distributed binary classifiers. We treat the problem of re-identification as an open-world problem, and address novelty detection and forgetting. As there are many tradeoffs in design and operation of such a system, we propose a set of evaluation measures to be used in addition to the recognition performance. The proposed concept is illustrated and evaluated on a new many-camera surveillance dataset and SAIVT-SoftBio dataset.
COBISS.SI-ID: 10896980