Abstract Easily accessible technologies, such as drones equipped with diverse onboard sensors, have greatly expanded opportunities to study animal behavior in natural environments. However, analyzing large volumes of unlabeled video data, often spanning hours, remains a significant challenge for machine learning, particularly in computer vision. Existing approaches typically process only a small number of frames, and accurate georeferencing of tracked positions is still largely unresolved, particularly in dynamic environments where static landmarks cannot be established. In this work, we focus on long-term tracking of animal behavior in real-world geographic coordinates. To address this challenge, we utilize classical probabilistic methods for state estimation, such as particle filtering. Particle filters offer a useful algorithmic structure for recursively adding new incoming information and thus ensuring time consistency. By incorporating recent developments in semantic object segmentation, we enable continuous tracking of rapidly evolving object formations, even in scenarios with limited data availability. We propose a novel approach for tracking schools of fish in the open ocean from drone videos. Our framework not only performs classical object tracking in image coordinates, instead it additionally tracks the position and spatial expansion of the fish school in geographic coordinates by fusing video data and the drone’s on board sensor information (GPS and IMU). No landmarks with known geographic coordinates are required, making the proposed method adaptable to unstructured, dynamic environments like the open ocean, where static landmarks are unavailable. With this, the presented framework enables researchers to study the collective behavior of fish schools within their social and environmental context.

Herein, we study the spectral coexistence of Geostationary (GEO) Fixed Satellite Services (FSS) downlink and Broadcasting Satellite Services (BSS) feeder links in the Ka-band (17.3 – 18.1 GHz) which is primarily allocated for BSS feeder links. Firstly, a novel cognitive spectrum exploitation framework is proposed in order to utilize the available band efficiently. Subsequently, based on the interference analysis carried out between these systems, two cognitive approaches, namely Carrier Allocation (CA) and Beamforming (BF), are investigated under the considered framework assuming the availability of an accurate Radio Environment Map (REM). The employed techniques allow the flexibility of using additional shared carriers for the FSS downlink system along with the already available exclusive carriers (19.7 – 20.2 GHz), thus increasing the overall system throughput. It is shown that a significant improvement in the per beam throughput as well as in the beam availability can be achieved by applying CA and BF approaches in the considered scenario.

Multi-User Detection (MUD) techniques are currently being examined as promising technologies for the next generation of broadband, interactive, multibeam satellite communication (SatCom) systems. Results in the existing literature have shown that when full frequency and polarization reuse is employed and user signals are jointly processed at the gateway, more than threefold gains in terms of spectral efficiency over conventional systems can be obtained. However, the information theoretic results for the capacity of the multibeam satellite channel are given under ideal assumptions, disregarding the implementation constraints of such an approach. Considering a real system implementation, the adoption of full resource reuse is bound to increase the payload complexity and power consumption. Since these novel techniques require extra payload resources, fairness issues in the comparison among the two approaches arise. The present contribution evaluates in a fair manner, the performance of the return link (RL) of a SatCom system serving mobile users that are jointly decoded at the receiver. In this context, the throughput performance of the assumed system is compared to that of a conventional one, under the constraint of equal physical layer resource utilization; thus the comparison can be regarded as fair. Results show, that even when systems operate under the same payload requirements as the conventional systems, a significant gain can be realized, especially in the high SNR region. Finally, existing analytical formulas are also employed to provide closed form descriptions of the performance of clustered systems, thus introducing insights on how the performance scales with respect to the system parameters.

This paper presents a radio interface recently standardised by ETSI under the name of S-MIM (S-band Mobile Interactive Multimedia) and especially designed to provide messaging services over GEO satellites using low-power terminals.

We address fixed satellite broadcast reception with the goal of decreasing the aperture of the receiving antenna. The front-end antenna size is commonly determined by the presence of interference from adjacent satellites. A small antenna aperture leads to interference from neighboring satellites utilizing the same frequency bands. We propose a reception system with M multiple input elements and with subsequent joint detection of desired and interfering signals that provides reliable communication in the presence of multiple interfering signals. An iterative least squares technique is adopted combining spatial and temporal processing and achieving robustness against pointing errors. Simulation results show how the proposed joint spatial and temporal adapted mechanism outperforms the simple combination of existing techniques under interference overloaded conditions. Also, we demonstrate how to accurately synchronize the signals as part of the detection procedure. The technique is evaluated in a realistic simulation study representing the conditions encountered in a DVB-S2 broadcast scenario.

Spectral efficiency is of great concern in the return channel of satellite based broadband systems. In (Beidas, 2002) the feasibility of increased efficiency by reducing channel spacing below the symbol rate was demonstrated using joint detection and decoding for a synchronized system. We extend this work by addressing the critical synchronization problem in the presence of adjacent channel interference (ACI) which limits performance as carrier spacing is reduced. A pilot sequence aided joint synchronization scheme for a multi-frequency time division multiple access (MF-TDMA) system is proposed. Based on a maximum likelihood (ML) criterion, the channel parameters, including frequency, time and phase are jointly estimated for the channel of interest and the adjacent channels. The impact of ACI on the synchronization and detection performance is investigated. It is shown that joint channel parameter estimation outperforms single carrier synchronization with reasonable additional computational complexity in the receiver. Based on the proposed synchronization scheme in conjunction with an appropriate joint detection mechanism, see (Beidas, 2002), carrier spacing can be reduced significantly compared to current systems providing a substantial increase in spectral efficiency.

The recently introduced multislice data acquisition for computed tomography (CT) is based on multirow detector design, increased rotation speed, and advanced z-interpolation and z-filtering algorithms. We evaluated slice sensitivity profiles (SSPs) and noise of a clinical multislice spiral CT (MSCT) scanner with M = 4 simultaneously acquired slices and adaptive axial interpolator (AAI) reconstruction software. SSPs were measured with a small gold disk of 50 microm thickness and 2-mm diameter located at the center of rotation (COR) and 100 mm off center. The standard deviation of CT values within a 20-cm water phantom was used as a measure of image noise. With a detector slice collimation of S = 1.0 mm, we varied spiral pitch p from 0.25 to 2.0 in steps of 0.025. Nominal reconstructed slice thicknesses were 1.25, 1.5, and 2.0 mm. For all possible pitch values, we found the full-width at half maximum (FWHM) of the respective sensitivity profile at the COR equivalent to the selected nominal slice thickness. The profiles at 100 mm off center are broadened less than 7 % on the average compared with the FWHM at the COR. In addition, variation of the full-width at tenth maximum (FWTM) at the COR was below 10% for p < or = 1.75. Within this range, image noise varied less than 10% with respect to the mean noise level. The slight increase in measured slice-width above p = 1.75 for nominal slice-widths of 1.25 and 1.50 mm is accompanied by a decrease of noise according to the inverse square root relationship. The MSCT system that we scrutinized provides reconstructed slice-widths and image noise, which can be regarded as constant within a wide range of table speeds. With respect to this, MSCT is superior to single-slice spiral CT. These facts can be made use of when defining and optimizing clinical protocols: the spiral pitch can be selected almost freely, and scan protocols can follow the diagnostic requirements without technical restrictions. In summary, MSCT offers constant image quality while scan times are reduced drastically. Volume scans with three-dimensional (3-D) isotropic resolution are routinely feasible for complete anatomical regions.

This paper presents the adaptive axial interpolator (AAI), a novel spiral interpolation approach for multislice spiral computed tomography (CT) implemented in a clinical multislice CT scanner, the SOMATOM Volume Zoom (Siemens Medical Systems, Forchheim, Germany). The method works on parallel-beam data generated from the acquired fan-beam data by azimuthal rebinning. Spiral interpolation is performed by distance-dependent weighting; i.e., for each ray, its distance to the image plane is evaluated and serves as an argument to a freely selectable weighting function, resulting in a weight factor. A normalization step is applied to the weight factors to ensure that the sum of all corresponding weights (i.e., the weights applied to rays that contribute to the same ray in the interpolated sinogram) is 1. By selection of appropriate weighting functions and suitable adjustment of the tube current, it is possible to keep the slice sensitivity profiles (SSP) as well as the pixel noise constant for all pitch values in the relevant range. Also, a large range of slice-thickness can be reconstructed from a given collimation. The method is, thus, very versatile. Further advantages are that it uses the entire applied dose for imaging and allows for efficient implementation using a table lookup approach.

The increasing importance of networks and the growing numbers of devices and services that run on them necessitate effective network and systems management. The traditional centralized management paradigm alone is no longer sufficient for effective management solutions, primarily as it does not scale well. Distribution of management tasks is a promising approach. The distributed management framework (DMF) presented in this paper provides an environment which allows a broad range of management tasks to move and run anywhere within the managed system. In our approach, management tasks are lightweight applications that can be dynamically configured and downloaded as required, reducing the load on managed resources and simplifying the problem of management software updates. We present an object-oriented, Java-based implementation of the DMF and describe applications developed on this platform.