Abstract
For docking manoeuvres, the detection of the objects to dock needs to be precise as the minimum deviation from the objective may lead to the failure of this task. The objective of this article is to test possible ways to detect a landmark using a laser rangefinder for docking manoeuvres. We will test a beacon-based localisation algorithm and an algorithm based on natural landmarks already implemented, however, we will apply modifications to such methods. To verify the possibility of docking using these methods, we will conduct experiments with a real robot.

Abstract

Abstract
To gain competitive advantage in today's mobile market, cellular network testing, monitoring and improving customer experience is crucial. Today independent benchmarking companies are hired by mobile operators to run drive tests in a certain geographical areas. The high cost for running these tests results in a low frequency of execution, typically this benchmarking is executed no more than two or three times per year, which is not sufficient to follow the dynamics of an LTE network in a dense urban area. The majority of the drive testing costs come from the car, driver, and the in-car technician. Another approach is to take advantage of existing transportation companies to carry on network benchmarking services to Mobile Network Operators. Unattended measurement nodes can be deployed in existing transportation fleets without the need for dedicated field personnel, reducing the cost of testing up to 70%. This demo uses nodes placed in buses, available in several cities in Europe, to create and validate an automatic LTE network benchmark. The tool allows an easy comparative analyses of mobile network quality of Service and quality of experience parameters based on the operators raw data.

Abstract
Cardiac volume/function assessment remains a critical step in daily cardiology, and 3-D ultrasound plays an increasingly important role. Fully automatic left ventricular segmentation is, however, a challenging task due to the artifacts and low contrast-to-noise ratio of ultrasound imaging. In this paper, a fast and fully automatic framework for the full-cycle endocardial left ventricle segmentation is proposed. This approach couples the advantages of the B-spline explicit active surfaces framework, a purely image information approach, to those of statistical shape models to give prior information about the expected shape for an accurate segmentation. The segmentation is propagated throughout the heart cycle using a localized anatomical affine optical flow. It is shown that this approach not only outperforms other state-of-the-art methods in terms of distance metrics with a mean average distances of 1.81 +/- 0.59 and 1.98 +/- 0.66 mm at end-diastole and end-systole, respectively, but is computationally efficient (in average 11 s per 4-D image) and fully automatic.

Abstract
Studies on entrepreneurial intentions often neglect the heterogeneity of individuals' education background. This paper develops an integrated intention-based framework and analyzes the impact of fields of study on entrepreneurial intentions. Based on a sample of 2423 final-year students, enrolled in 32 fields of study, and resorting to logistic estimations, we find that, beside the attitude towards starting a business, fields of study, considered at a highly detailed level, are relevant (direct and indirect) predictors of entrepreneurial intention. We unambiguously show that there is a huge hidden potential for new venture creation in fields of study related to creative and leisure activities (e.g., Arts and humanities, or, more specifically, Literature and linguistics, History and archaeology, Audio-visual techniques and media production, Sports, and Architecture and town planning), Law, and Health (most notably, Pharmacy and Veterinary). Significant differences in the level of intention between students of different fields of study indicate that universities should more extensively focus entrepreneurship education on students in other subject area than business or engineering/technology sciences.

Abstract
During the last few years an increasing focus has been made by the research community in utilizing wireless sensor networks (WSNs) in an abundant variety of different applications. Such types of sensor networks are usually supplied by non-rechargeable batteries in order to reduce the expenses. Multi-hop wireless sensor networks frequently utilize a time-division multiple-access (TDMA) plan with the purpose to systematically gather data from various positions of an extended region. The proposed access methods for the Medium Access Control (MAC) in this study combine hybrid proprieties. The proposed MAC specifies that in a given time interval the access to the medium has to be entirely free and without restrictions between the exterior nodes. While this event lasts, the nodes compete for a slot in the network. The proposed methodology corresponds to time-division hybrid multiple-access (TDHMA).