The purpose of this paper is to examine the impact of higher education services quality dimensions on student satisfaction and loyalty using an example of a private university in a developing country. On a sample of 265 students, using a covariance-based structural equation modeling, we test a proposition that satisfaction fully mediates the effect of service quality dimensions, using a SERVPERF instrument, on loyalty. The results show a positive relationship between each quality dimension and satisfaction, as well as a complete lack of direct effect of quality dimensions on loyalty. This shows that satisfaction in higher education serves as a vehicle that drives the effects of quality on loyalty. Research implications and limitations are discussed and explained in the study.

Air traffic assignment to departure and arrival routes has a major impact on the population noise exposure in the vicinity of the airport. In some cases, by choosing the suitable air traffic assignment it is possible to avoid overflying populated areas and reduce number of people affected by noise. However, such an approach almost always leads to an increase in route length, and therefore an increase in fuel consumption and CO2 emissions. Although aircraft noise and fuel consumption reduction are conflicting goals, they both represent pivotal aspects of air transport sustainable development. In this paper, the methods of multi-criteria optimisation are applied, which are generally used when it is necessary to make an optimal decision that requires a compromise (trade-off) solution between two or more conflicting goals. This research aims to develop a mathematical model and to propose an algorithm for air traffic assignment to departure and arrival routes that will, through the Pareto optimality concept, find the approximation of a set of nondominated solutions that minimize population noise exposure and fuel consumption. The approach was demonstrated on Belgrade airport to show the benefits of the proposed model on a real data example. Since all Pareto optimal solutions are considered equally good, from all obtained air traffic assignments, the three representative solutions were compared to the actual air traffic assignment (Base case). The obtained results indicate that the proposed approach can provide solutions which offer a good trade-off between the concerned metrics.

The purpose of this study is to examine links between, on the one hand, employee satisfaction, loyalty and performance, and on the other, the relationship between customer satisfaction and loyalty, as well as their inter-relationship. We conducted a study with employees (53 employees) and students (262 students) across seven departments of a private university in a developing European country. In order to test the cross-level effects of employee-level constructs on student-level constructs, a multilevel analysis was conducted using hierarchical linear modeling. The results confirmed the positive effect of employee satisfaction on employee loyalty and employee performance, but not the impact of the employees’ loyalty on their performances. At the same time, the results showed that students’ satisfaction was positively related to loyalty. Finally, the results showed that, unlike employee performance, employee loyalty at the level of the department had a positive and significant impact on the students’ loyalty and also enhanced the effect of students’ satisfaction

Introduction: The purpose of this study to investigate internal service quality (as perceived by employees) and external (customer) perceptions of quality in the context of service profit chain (SPC).Objective: The objective of the study is to evaluate the impact of internal service quality on students’ perceptions of quality and to test the significance of a direct link between internal and external service quality.Methods: We measured the perceived service quality using a SERVPERF instrument and the multilevel modeling approach with HLM 7.01.Results: The empirical findings support a link between perceptions of internal and external service quality. We show that when employees (faculty) perceive university services as being of high quality, it has a positive spill-over effect on students’ overallperceptions of the quality of university services. Perceptions of internal service quality are also positively related to students’ perceptions of reliability, responsiveness and quality assurance.Conclusions: The perceptions of internal service quality by faculty members are positively related to students’ perceptions of quality. Comparing the levels of internal and external service quality will help managers define priorities for allocating resources to improve quality.

Support to reviewing implementation of Acceptable Level of Safety Performance (ALoSP) concept in EUROCONTROL Member States and development of an initial definition and guidance.

It is widely accepted that the most significant local environmental impact associated with the operation of airports arises from the noise generated by aircraft. In order to mitigate negative effect of noise, many airports have introduced a variety of measures. Although there are similarities between airports that are introducing some of the noise abatement measures (NAMs), the number and type of applied measures are very different among them. The research presented in this paper focuses on finding statistical evidence to support hypothesis that there is a significant correlation between implemented NAMs and specific characteristics related to airports. In order to determine the most influential factors for the introduction of NAMs in airport surroundings, logistic regression was used on data set for 246 European airports. For predictor variables, five specific characteristics related to airports (number of runways and aircraft operations, distance from the city and the population of the city that it serves, GDP per capita) and ten NAMs as a dichotomous variables have been used. The results of analyses have shown that there is a significant correlation between implemented NAMs and specific characteristics related to airports but also between NAMs themselves. The results of this research can be used to determine the likelihood of introduction of certain NAM for each airport based on the factors that showed significant correlation with that NAM.

: The main goal of this paper is to embed a watermark in the speech signal, using the three techniques such as Discrete Cosine Transform (DCT) along with Singular Value Decomposition (SVD) and Discrete Wavelet Transform (DWT).In this paper, various combinations were tried for embedding the watermark image into the audio signal such as DWT and SVD, DCT with SVD and DCT, DWT with SVD. Their performance was evaluated based on Signal to Noise Ratio (SNR) and Bit Error Rate (BER). From the results it can be seen that the combination of DCT with DWT and SVD method provides better result.

Our Genomic Relevance Parameterization (GReP) model aims to explore a possible relationship between gene expression values from breast cancer patients and mathematical tumor growth modeling parameters calculated using data from clinical and preclinical measurements. We introduce two methods to relate genomic information and the tumor growth measurements. One method explores the impact of exponentiation of gene expression values, whereas the other utilizes the correlation between co-regulated genes and the growth parameters. As inputs to our GReP model, we used patient tumor volume measurements and genomic information for 74 breast cancer related genes from the I-SPY 1 TRIAL. We performed a preliminary validation of GReP model using experimental data from literature including MDA-MB-231 cell line, MDA-MB-231 cell line with CXCL12 gene over-expressed, and the MDA MB-231 sub-cell lines 1834 and 4175. Tumor growth curves generated by GReP model, for the initial exponential phase of tumor growth, closely match the pre-clinical data reported in the literature. These promising results show that it may be possible to build tools combining clinical information and genomic data to model cancerous tumor growth.

The creation of personal and individualized anti-cancer treatments has been a major goal in the progression of cancer discovery as evident by the continuous research efforts in genetics and population based PK/PD studies. In this paper we use our clinical decision support tool, called ChemoDSS, to evaluate the effectiveness of three treatments recommended by the NCCN guidelines for ovarian cancer using pre-clinical data from the literature. In particular, we analyze the treatments of PC (i.e., Paclitaxel and Cispaltin), DC (i.e., Docetaxel and Carboplatin), and PBC (i.e., Paclitaxel, Bevacizumab, and Carboplatin). Our in silico analysis of the ovarian cancer treatments shows that PC was the most effective regimen for treating ovarian cancer compared to DC and PBC, which is consistent with literature findings. We demonstrate that we can successfully evaluate the effectiveness of the selected ovarian cancer treatment regimens using ChemoDSS.

Cancer treatment has continually evolved towards the personalized selection and delivery of anticancer therapies. In this paper we evaluate the effectiveness of three treatments recommended by the NCCN guidelines for HER2-positive breast cancer using our clinical decision support tool called ChemoDSS. For our in silico analysis, we used pre-clinical data from the literature for HER2 transfected MCF7 human breast cancer xenografts in athymic mice. In particular, we analyzed the expected effects for the multi-drug treatments of AC-TH (i.e., Doxorubicin and Cyclophosphamide followed by Paclitaxel and Trastuzumab), TCH (i.e., Docetaxel, Carboplatin, and Trastuzumab), and TH (i.e., Docetaxel and Trastuzumab). Our results show that, using the pharmacokinetic (PK) and pharmacodynamic (PD) characteristics of the reported pre-clinical data, AC-TH appears to be the most effective regimen for treating this occurrence of breast cancer compared to TCH and TH. This result is consistent with literature findings for HER2 transfected MCF7 breast cancer xenografts, and demonstrates the effectiveness of various treatments recommended by the NCCN guidelines for HER2-positive breast cancer. We plan to incorporate various genetic markers into ChemoDSS, and verify existing and novel treatment regimens for different types of cancers.