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Arash Pishravian and Masoud Reza Aghabozorgi Sahaf

Source Separation by Adaptive Estimation of Score Function Difference, Proceedings of ICA 2004, Granada, Spain, 2004, pp. 9-17. [15] VLASSIS, N.-MOTOMURA, Y. : Efficient Source Adaptivity in Independent Component Analysis, IEEE Transaction on Neural Networks 12 No. 3 (2001), 559-566. [16] BABAIE-ZADE, M.-JUTTEN, C. : A General Approach for Mutual Information Minimization and its Application to Blind Source Separation, Signal Processing 85 No. 5 (2005), 975-995. [17] AMARI, S.-CICHOCKI, A.-YANG, H. H. : A New Learning

Open access

Małgorzata Kowalczyk and Czesław Niżankowski

Occupational Hazard Management at the Grinding Station

The paper demonstrates the usefulness of the Risk Score method for risk management at professional grinding stations, taking into account the nature of the station's operations. The adoption of consistent processes within a comprehensive framework helps to ensure that risk is managed effectively, efficiently and coherently across the organization. The approach described in this paper introduces the principles and guidelines for managing safety risk in an orderly, transparent and credible manner. The aim of the present study is to reduce occupational hazard at grinding stations.

Open access

Insu Song, John Vong, Nguwi Yok Yen, Joahchim Diederich and Peter Yellowlees

Abstract

In this study, we propose to diagnose facial nerve palsy using Support Vector Machines (SVMs) and Emergent Self-Organizing Map (ESOM). This research seeks to analyze facial palsy domain using facial features and grade the degree of nerve damage based on the House-Brackmann score. Traditional diagnostic approaches involve a medical doctor recording a thorough history of a patient and determining the onset of paralysis, rate of progression and so on. The most important step is to assess the degree of voluntary movement of the facial nerves and document the grade of facial paralysis using House- Brackmann score. The significance of the work is the attempt to understand the diagnosis and grading processes using semi-supervised learning with the aim of automating the process. The value of the research is in identifying and documenting the limited literature seen in this area. The use of automated diagnosis and grading greatly reduces the duration of medical examination and increases the consistency, because many palsy images are stored to provide benchmark references for comparative purposes. The proposed automated diagnosis and grading are computationally efficient. This automated process makes it ideal for remote diagnosis and examination of facial palsy. The profiling of a large number of facial images are captured using mobile phones and digital cameras.

Open access

Md Wasiur Rahman, Fatema Tuz Zohra and Marina L. Gavrilova

Abstract

Computational intelligence firmly made its way into the areas of consumer applications, banking, education, social networks, and security. Among all the applications, biometric systems play a significant role in ensuring an uncompromised and secure access to resources and facilities. This article presents a first multimodal biometric system that combines KINECT gait modality with KINECT face modality utilizing the rank level and the score level fusion. For the KINECT gait modality, a new approach is proposed based on the skeletal information processing. The gait cycle is calculated using three consecutive local minima computed for the distance between left and right ankles. The feature distance vectors are calculated for each person’s gait cycle, which allows extracting the biometric features such as the mean and the variance of the feature distance vector. For Kinect face recognition, a novel method based on HOG features has been developed. Then, K-nearest neighbors feature matching algorithm is applied as feature classification for both gait and face biometrics. Two fusion algorithms are implemented. The combination of Borda count and logistic regression approaches are used in the rank level fusion. The weighted sum method is used for score level fusion. The recognition accuracy obtained for multi-modal biometric recognition system tested on KINECT Gait and KINECT Eurocom Face datasets is 93.33% for Borda count rank level fusion, 96.67% for logistic regression rank-level fusion and 96.6% for score level fusion.

Open access

J. Piątkowski and P. Kamiński

Abstract

The FMEA (Failure Mode and Effects Analysis) method consists in analysis of failure modes and evaluation of their effects based on determination of cause-effect relationships for formation of possible product or process defects. Identified irregularities which occur during the production process of piston castings for internal combustion engines were ordered according to their failure rates, and using Pareto-Lorenz analysis, their per cent and cumulated shares were determined. The assessments of risk of defects occurrence and their causes were carried out in ten-point scale of integers, while taking three following criteria into account: significance of effects of the defect occurrence (LPZ), defect occurrence probability (LPW) and detectability of the defect found (LPO). A product of these quantities constituted the risk score index connected with a failure occurrence (a so-called “priority number,” LPR). Based on the observations of the piston casting process and on the knowledge of production supervisors, a set of corrective actions was developed and the FMEA was carried out again. It was shown that the proposed improvements reduce the risk of occurrence of process failures significantly, translating into a decrease in defects and irregularities during the production of piston castings for internal combustion engines.

Open access

Darie Moldovan and Mircea Moca

References [1] Tobin, J: A General Equilibrium Approach To Monetary Theory. Journal of Money, Credit and Banking (1) pp.15–29 (1969) [2] Altman, E. I., Saunders, A.: Credit risk measurement: Developments over the last 20 years. Journal of banking & finance, 21(11), pp. 1721-1742 (1997). [3] Weimin Chen, Guocheng Xiang, Youjin Liu, Kexi Wang, Credit risk Evaluation by hybrid data mining technique, Systems Engineering Procedia, 3 (2012) [4] Kambal, E.; Osman, I.; Taha, M.; Mohammed, N.; Mohammed, S. Credit scoring using data mining

Open access

Yoichi Hayashi, Yuki Tanaka, Tomohiro Takagi, Takamichi Saito, Hideaki Iiduka, Hiroaki Kikuchi, Guido Bologna and Sushmita Mitra

References [1] Marqus, A.I., Garca, V., & Snchez, J.S. On the suitability of resampling techniques for the class imbalance problem in credit scoring. Journal of the Operational Research Society 64, pp. 1060–1070, 2013. [2] Zhao Z., Xu, S., Kang, B. H., Kabir, M. M. J., & Liu, Y. Investigation and improvement of multilayer perceptron neural networks for credit scoring Expert Systems with Applications 42, pp. 3508–3516, 2015 [3] Finlay, S. M. Multiple classifier architectures and their applications to credit risk assessment. European Journal of

Open access

Attila Bölcskei, András Zsolt Kovács and Domen Kušar

Abstract

Spatial ability development is of paramount importance in engineering training, especially for architects. The paper aims to compare results achieved by the world-wide Mental Rotation Test (MRT) at the University of Ljubljana and at the Ybl Faculty of SzIU in Budapest, with respect to total scores, improvement and hand preferences. The paper concludes that the mental rotation aspect of spatial intelligence can significantly be developed by Descriptive Geometry courses in both countries. Sophisticated statistical analysis, however, leads to new ideas in scoring MRT. The main goal of the paper is to present an alternative scoring system, which seems to be fairer and provides the expected statistical behavior of samples.

Open access

Transport and Telecommunication Journal

The Journal of Transport and Telecommunication Institute

Open access

Paul Woolliscroft, Dagmar Caganova, Milos Cambal and Jana Makraiova

Abstract

The need to develop a clear understanding of multicultural competencies is essential to fully develop a strategic approach to human capital management (HCM). As Slovak workplaces become more diverse, culture and intercultural management has gained greater significance and the adoption of a strategic approach is now critical to the success and competitive advantage of the organisation. Moreover, it is necessary to address this field of management to ensure the high performance of organisations, especially those operating within a global setting. The focus of the research is on the identification of multicultural competencies in the context of Slovak industrial enterprises to measure and identify linkages between cultural aspects and the strategic business performance.