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The integration of satellite and terrestrial networks has become inevitable in the next generations of communications networks due to emerging needs of ubiquitous connectivity of remote locations. New and existing services and critical infrastructures in remote locations in sea, on land and in space will be seamlessly connected through a diverse set of terrestrial and non-terrestrial communication technologies. However, the integration of terrestrial and non-terrestrial systems will open up both systems to unique security challenges that can arise due to the migration of security challenges from one to another. Similarly, security challenges can also arise due to the incompatibility of distinct systems or incoherence of security policies. The resulting security implications, thus, can be highly consequential due to the criticality of the infrastructures such as space stations, autonomous ships, and airplanes, for instance. Therefore, in this article we study existing security challenges in satellite-terrestrial communication systems and discuss potential solutions for those challenges. Furthermore, we provide important research directions to encourage future research on existing security gaps.

Finite element (FE) modeling is becoming an increasingly popular method for analyzing knee joint mechanics and biomechanical mechanisms leading to osteoarthritis (OA). The most common and widely available imaging method for knee OA diagnostics is planar X-ray imaging, while more sophisticated imaging methods, e.g., magnetic resonance imaging (MRI) and computed tomography (CT), are seldom used. Hence, the capability to produce accurate biomechanical knee joint models directly from X-ray imaging would bring FE modeling closer to clinical use. Here, we extend our atlas-based framework by generating FE knee models from X-ray images (N = 28). Based on measured anatomical landmarks from X-ray and MRI, knee joint templates were selected from the atlas library. The cartilage stresses and strains of the X-ray-based model were then compared with the MRI-based model during the stance phase of the gait. The biomechanical responses were statistically not different between MRI- vs. X-ray-based models when the template obtained from X-ray imaging was the same as the MRI template. However, if this was not the case, the peak values of biomechanical responses were statistically different between X-ray and MRI models. The developed X-ray-based framework may pave the way for a clinically feasible approach for knee joint FE modeling.

Correction to: Jahangir, S., Mohammadi, A., Mononen, M.E. et al. Rapid X-Ray-Based 3-D Finite Element Modeling of Medial Knee Joint Cartilage Biomechanics During Walking. Ann Biomed Eng 50, 666–679 (2022). https://doi.org/10.1007/s10439-022-02941-0 Rinnakkaistallennettu versio / Self-archived version

Main research and development interest of 5G and beyond systems are focusing on solution for populated and hot spot areas, but public safety authorities need reliable communication solutions in rural and remote areas. Tactical bubbles—ad hoc-type nonpublic communications networks built with the 3rd Generation Partnership Project-based mobile technologies—offer mission critical communications services for public safety authorities in areas with bad mobile network coverage while also providing additional capacity in hot spot areas. In this experimental study, three interconnected bubbles acting on three different frequency bands—2.3 GHz (40), 2.6 GHz (7), and 3.5 GHz (n78)—are trialed. This article provides the analysis of different factors related to performance and user experience of tactical bubbles. Both ground-level and aerial trial measurements, as well as simulations, were utilized to verify our configuration for the tactical bubbles and their fulfillment of the quality requirements. The performance and coverage of the tactical bubbles are evaluated in a trial, which represents authorities’ search operations in a rural environment with hills, forests, and swamps. The achieved coverage range of the bubbles is more than 1000 m with the unmanned aerial system-based measurements, whereas by car, the coverage is less than 600 m. The effect of obstacles (ie, buildings and hills) on the coverage area and performance of bubbles is significant, especially on car-based measurements on the ground level.

The need for high-quality communications networks is urgent in data-based farming. A particular challenge is how to achieve reliable, cost-efficient, secure, and broadband last-mile data transfer to enable agricultural machine control. The trialed ad hoc private communications networks built and interconnected with different alternative wireless technologies, including 4G, 5G, satellite and tactical networks, provide interesting practical solutions for connectivity. A remotely controlled tractor is exemplified as a use case of machine control in the demonstrated private communication network. This paper describes the results of a comparative technology analysis and a field trial in a realistic environment. The study includes the practical implementation of video monitoring and the optimization of the control channel for remote-controlled unmanned agricultural tractors. The findings from this study verify and consolidate the requirements for network technologies and for cybersecurity enablers. They highlight insights into the suitability of different wireless technologies for smart farming and tractor scenarios and identify potential paths for future research.

5G enables the use of different types of services over the same physical infrastructure through the concepts and technologies of virtualization, softwarization, network slicing and cloud computing. Mobile Virtual Network Operators (MVNOs), using these concepts, provide an opportunity to share the same physical infrastructure among multiple operators. Each MVNO can have own distinct operating and support systems. However, the technologies used to enable such an environment have their own explicit security challenges and solutions. The integrated environment built upon these novel concepts and technologies, thus, will have complex security implications and requirements to be satisfied. In this vain, this article provides an overview of the security challenges and potential solutions for MVNOs.

The forthcoming communication networks for public safety authorities rely on the fifth generation (5G) of mobile networking technologies. Police officers, paramedics, border guards, as well as fire and rescue personnel, will connect through commercial operator’s access network and rapidly deployable tactical bubbles. This transition from closed and dedicated infrastructure to hybrid architecture will expand the threat surface and expose mission-critical applications and sensitive information to cyber and physical adversaries. We explore and survey security architecture and enablers for prioritized public safety communication in 5G networks. We identify security threat scenarios and analyze enabling vulnerabilities, threat actors, attacks vectors, as well as risk levels. Security enablers are surveyed for tactical access and core networks, commercial infrastructure, and mission-critical applications, starting from push-to-talk and group video communication and leading to situational-awareness and remote-controlled systems. Two solutions are trialed and described in more detail: remote attestation enhanced access control for constrained devices, and securing of satellite backhauls. We also discuss future research directions highlighting the need for enablers to automate security of rapid deployments, for military-grade cost-effective customizations of commercial network services to ensure robustness, and for hardening of various types of public safety equipment.

Background: Finite element modelling can be used to evaluate altered loading conditions and failure locations in knee joint tissues. One limitation of this modelling approach has been experimental comparison. The aims of this proof-of-concept study were: 1) identify areas susceptible to osteoarthritis progression in anterior cruciate ligament reconstructed patients using finite element modelling; 2) compare the identified areas against changes in T₂ and T₁ₚ values between 1-year and 3-year follow-up timepoints. Methods: Two patient-specific finite element models of knee joints with anterior cruciate ligament reconstruction were created. The knee geometry was based on clinical magnetic resonance imaging and joint loading was obtained via motion capture. We evaluated biomechanical parameters linked with cartilage degeneration and compared the identified risk areas against T₂ and T₁ₚ maps. Findings: The risk areas identified by the finite element models matched the follow-up magnetic resonance imaging findings. For Patient 1, excessive values of maximum principal stresses and shear strains were observed in the posterior side of the lateral tibial and femoral cartilage. For Patient 2, high values of maximum principal stresses and shear strains of cartilage were observed in the posterior side of the medial joint compartment. For both patients, increased T₂ and T₁ₚ values between the follow-up times were observed in the same areas. Interpretation: Finite element models with patient-specific geometries and motions and relatively simple material models of tissues were able to identify areas susceptible to post-traumatic knee osteoarthritis. We suggest that the methodology presented here may be applied in large cohort studies.

Many natural land surfaces, such as sand or snow, consist of densely packed grains, often covered by dust, water droplets, contaminated with other materials such as possible oil leaks, hoar frost, and can also be internally cracked, porous, and heterogeneous. Most scattering models ignore these complications, but here a more detailed approach is taken to test all these effects. The current model is composed of three techniques: 1) Monte Carlo-based electromagnetic volume integral equation technique for non-spherical wavelength scale dust particles, 2) Monte Carlo ray tracing for stochastic-shaped grains much larger than the wavelength, with optional point scattering from dust cover, internal inclusions, and liquid surface layer, in a layer of an optical depths of few units, and 3) adding-doubling to combine smaller layers into an arbitrary, thick and vertically inhomogeneous medium. The model allows the medium to be built in a modular way, and after initialisation, rather complicated layered structures can be computed quickly and flexibly. The computed results are compared against experimental measurements of snow and sand. The model agrees with measurements usually within the measurement accuracy (∼ 0:05). The scattering is observed to depend significantly on grain size, shape, orientation, composition, fine structures, dust, and some other properties that need to be defined. Both, measurement and modelling, require much deeper attention to these properties. © 2020 Copernicus GmbH. All rights reserved.

Commercial mobile operators’ networks will be used for public safety communications due to demand for wireless broadband services, new applications, and smart devices. Existing dedicated professional mobile radio networks, such as terrestrial trunked radio, Tetrapol, and project 25, are based on narrowband technologies and hence their data bandwidth is limited. This paper studies how critical communications needed, e.g., by ambulance personnel, rescue squads, and law enforcement agencies can be implemented over a 5G network. The most important technology enablers are described and test network architectures used in our project given. We focus on two different use cases. First, how to enable priority communications over a commercial mobile network. Second, how to create rapidly deployable networks for emergency and tactical operations. Tests done with the implemented systems in real networks show that both approaches are very promising for future critical users. Techniques such as network slicing and licensed shared access provide means to support mission critical applications in any environment.

Productivity of cropping systems can be constrained simultaneously by different limiting factors and approaches allowing to indicate and identify plants under stress in field conditions can be valuable for farmers and breeders. In organic production systems, sensing solutions are not frequently studied, despite their potential for crop traits retrieval and stress assessment. In this study, spectral data in the optical domain acquired using a pushbroom spectrometer on board of a unmanned aerial vehicle is used to evaluate the potential of this information for assessment of late blight (Phytophthora infestans) incidence on potato (Solanum tuberosum) under organic cultivation. Vegetation indices formulations with two and three spectral bands were tested for the complete range of the spectral information acquired (i.e., from 450 to 900 nm, with 10 nm of spectral resolution). This evaluation concerned the discrimination between plots cultivated with only one resistant potato variety in contrast with plots with a variety mixture, with resistant and susceptible cultivars. Results indicated that indices based on three spectral bands performed better and optimal wavelengths (i.e., near 490, 530 and 670 nm) are not only related to chlorophyll content but also to other leaf pigments like carotenoids.

During 2014–2015 we have developed a new method to measure reflectance factor anisotropy using a pushbroom spectrometer mounted on a multicopter UAV. In this paper/presentation we describe the acquisition method and show the preliminary results of the experiment. To validate the measurements the same targets have also been measured with a laboratory goniometer system. The first experiments over sugar beet fields in 2014 show similar trends in both UAV and laboratory anisotropy data, but also some differences caused by differences in sampling and diffuse illumination. In 2015 a more extensive study on wheat, barley and potato fields were performed. The measurements were repeated on three days over the growth of the crops allowing linking the development of the crops to the anisotropy signals. On each day the anisotropy measurement was repeated 4–5 times with different solar zenith angles ranging from 60° to 40° allowing analysis how the solar angle affects the anisotropy. The first results of these experiments will be presented in this conference.

Agricultural lands have strong impact on global carbon dynamics and nitrogen availability. Monitoring changes in agricultural lands require more efficient and accurate methods. The first prototype of a full waveform hyperspectral Light Detection and Ranging (LiDAR) instrument has been developed at the Finnish Geodetic Institute (FGI). The instrument efficiently combines the benefits of passive and active remote sensing sensors. It is able to produce 3D point clouds with spectral information included for every point which offers great potential in the field of remote sensing of environment. This study investigates the performance of the hyperspectral LiDAR instrument in nitrogen estimation. The investigation was conducted by finding vegetation indices sensitive to nitrogen concentration using hyperspectral LiDAR data and validating their performance in nitrogen estimation. The nitrogen estimation was performed by calculating 28 published vegetation indices to ten oat samples grown in different fertilization conditions. Reference data was acquired by laboratory nitrogen concentration analysis. The performance of the indices in nitrogen estimation was determined by linear regression and leave-one-out cross-validation. The results indicate that the hyperspectral LiDAR instrument holds a good capability to estimate plant biochemical parameters such as nitrogen concentration. The instrument holds much potential in various environmental applications and provides a significant improvement to the remote sensing of environment.