The application of thick-film technology in C-MEMS

Laminated 3D structures made using low-temperature co-fired ceramic (LTCC) technology are practical for ceramic micro-electro-mechanical systems (C-MEMS). The sensors for mechanical quantities, and/or actuators, are fundamental parts of MEMS. Thick-film resistors can be used to sense the mechanical deformations, and thick-film piezoelectric materials can be used as electro-mechanical transducers in a C-MEMS structure. The integration of these thick-film materials on LTCC substrates is in some cases difficult to realise due to interactions with the rather glassy LTCC substrates. The subject of our work is an investigation of thick-film materials for electro-mechanical transducers (sensors and actuators) and their compatibility with LTCC substrates. Resistors made with commercial thick-film resistor materials for use as sensors on LTCC substrates have been investigated and evaluated. Ferroelectric ceramic materials based on solid solutions of lead zirconate titanate (PZT) with low firing temperatures around 850°C were developed for thick-film technology and evaluated on LTCC substrates.     

A system identification approach to the modelling of pulsed eddy-current systems

The purpose of this article is to present a novel approach in the modelling of pulsed eddy-current systems. Frequency-domain finite element analysis is used to build up a z-domain, finite impulse response (FIR) model. The FIR model allows excitation to be varied without need for the field analysis to be performed again. Furthermore, the proposed approach to the modelling of the system function allows unequal spacing of the frequency samples. This enables greater accuracy of the modelling in the frequency range where the magnitude or phase response of the system varies greatly. The proposed approach was validated on a pulsed remote-field eddy-current system in a ferromagnetic tube. Excellent agreement between predicted and measured response was achieved.     

Bearings only single-sensor target tracking using Gaussian mixtures

This paper presents a new approach for single sensor tracking using passive bearings only measurements. Gaussian mixture measurement presentation, together with a track splitting algorithm, allow space-time integration of the target position uncertainty with a simple algorithm. The bearings-only measurements are incorporated into track as they arrive using a dynamic bank of linear Kalman filters. While this approach is applicable to the case with the target detection, data association and multitarget issues, this paper concentrates on the target trajectory estimation using associated measurements. A simulation study demonstrates the benefits of this approach.     

Projection Model for Fusing the Information of Pythagorean Fuzzy Multicriteria Group Decision Making Based on Geometric Bonferroni Mean

As a new generalization of fuzzy sets, Pythagorean fuzzy sets (PFSs) can availably handle uncertain information more flexibly in the process of decision making. Through synthesizing the Bonferroni mean and the geometric mean, the geometric Bonferroni mean (GBM) captures the interrelationship of the input arguments. Considering the interrelationship among the input arguments, we introduce GBM into Pythagorean fuzzy situations and expand its applied fields. Under the Pythagorean fuzzy environment, we develop the Pythagorean fuzzy geometric Bonferroni mean and weighted Pythagorean fuzzy geometric Bonferroni mean (WPFGBM) operators describing the interrelationship between arguments and some special properties of them are also investigated. Then, we employ the WPFGBM operator to fuse the information in the Pythagorean fuzzy multicriteria group decision making (PFMCGDM) problem, which can obtain much more information in the process of group decision making. With the aid of the projection model, we present its extension and further design a new method for the application of PFMCGDM. Finally, an example is given to elaborate on the performance of our proposed method.     

Sustainable development of lignite production on open cast mines in Serbia

Energy sector represents a key industrial branch for national, environmental and economic success. With its exclusive access to domestic deposits, lignite industry represents a guarantor of reliable raw materials, offering long-term supply security based on verified reserves. Currently operated coalmines in Serbia (Kolubara and Kostolac) have production around 36 million tons of lignite, and over 108 million m3 of overburden. Consequently, sustainability of lignite production requires cost reduction and environmental protection, as well as capacity increase. In order to rationalise, and increase efficiency of Serbian lignite mines, it is necessary to focus the activities on major issues shown within the triangle of energy policy objectives (security of supply, competi-tive prices and environmental protection). Production process optimisation singled out several special programs. Equipment revi-talization and modernization is necessary taking into account that majority of the currently operated machinery has a life up to 25 years. Production process automation would enable high level of technical operation in the field of open cast mines management. Lack of coal quality uniformity is the permanent problem resulting by great amounts of coal reserves to be used uneconomically. Planning and training at all levels and finally cooperative software for business procedures and work order management. The measures suggested are a key precondition for maintaining competitive position of lignite production on international level.     

Exploring the influence of CAPTCHA types to the users response time by statistical analysis

CAPTCHA stands for Completely Automated Public Turing Test to Tell Computers and Humans Apart. It is a test program that solves a given task for preventing the attacks made by automatic programs. If the response to CAPTCHA is correct, then the program classifies the user as a human. This paper introduces a new analysis of the impact of different CAPTCHAs to the Internet user’s response time. It overcomes the limitations of the previous approaches in the state-of-the-art. In this sense, different types of CAPTCHAs are presented and described. Furthermore, an experiment is conducted, which is based on two populations of Internet users for text and image-based CAPTCHA types, differentiated by demographic features, such as age, gender, education level and Internet experience. Each user is required to solve the different types of CAPTCHA, and the response time to solve the CAPTCHAs is registered. The obtained results are statistically processed by Mann-Whitney U and Pearson’s correlation coefficient tests. They analyze 7 different hypotheses which evaluate the response time in dependence of gender, age, education level and Internet experience, for the different CAPTCHA types. It represents an invaluable study in the literature to predict the best use of a given CAPTCHA for specific types of Internet users.

     

Assessing the impact of meta-model evolution: a measure and its automotive application

Software and Systems Modeling - Domain-specific meta-models play an important role in the design of large software systems by defining language for the architectural models. Such common modeling...     

Interval‐valued Pythagorean fuzzy extended Bonferroni mean for dealing with heterogenous relationship among attributes

Owing to the information insufficiency, it might be difficult for decision makers to precisely evaluate their assessments in real decision‐making. As a new extension of the Pythagorean fuzzy sets, the interval‐valued Pythagorean fuzzy sets (IVPFSs) can availably provide enough input space for decision makers to evaluate their assessments with interval numbers. By extending the Bonferroni mean to model the heterogeneous interrelationship among attributes, the extended Bonferroni mean (EBM) was examined. Considering the partition structure of relationship among the attributes, we introduce the EBM into the interval‐valued Pythagorean fuzzy environment and develop two new aggregation operators, namely, interval‐valued Pythagorean fuzzy extended Bonferroni mean and weighted interval‐valued Pythagorean fuzzy extended Bonferroni mean (WIVPFEBM) operators. Meanwhile, some of their special cases and properties are also deeply discussed. Subsequently, by employing the WIVPFEBM operator, we propose an approach for multiple attribute decision making with IVPFSs. Finally, a practical illustration of the E‐commerce project selection problem is investigated by our proposed method, which successfully demonstrates the applicability of our results.     

Pythagorean fuzzy Bonferroni mean aggregation operator and its accelerative calculating algorithm with the multithreading

In this paper, we study the well‐known Bonferroni mean and develop its generalized aggregation operators in the Pythagorean fuzzy environment. More specifically, by considering the interrelationship between arguments with Pythagorean fuzzy information, we develop the Pythagorean fuzzy Bonferroni mean (PFBM) and some special properties and cases of them are also discussed. Furthermore, taking the multicriteria decision making environment into consideration, we extend the results of PFBM and develop the weighted Pythagorean fuzzy Bonferroni mean (WPFBM). Meanwhile, we also propose an approach for the application of WPFBM. However, during the application of the WPFBM operator, the calculation is very complex and time consuming. Hence, we introduce the multithreading into the application of the WPFBM operator and develop an accelerative calculating algorithm for it. To validate the performance of the accelerative calculating algorithm, we further design the corresponding experimental analysis.