Search results

The paper aims to solve the problem of personnel intrusion identification within the limits of high-speed railways. It adopts the fusion method of millimeter wave radar and camera to improve the accuracy of object recognition in dark and harsh weather conditions.

This paper adopts the fusion strategy of radar and camera linkage to achieve focus amplification of long-distance targets and solves the problem of low illumination by laser light filling of the focus point. In order to improve the recognition effect, this paper adopts the YOLOv8 algorithm for multi-scale target recognition. In addition, for the image distortion caused by bad weather, this paper proposes a linkage and tracking fusion strategy to output the correct alarm results.

Simulated intrusion tests show that the proposed method can effectively detect human intrusion within 0–200 m during the day and night in sunny weather and can achieve more than 80% recognition accuracy for extreme severe weather conditions.

(1) The authors propose a personnel intrusion monitoring scheme based on the fusion of millimeter wave radar and camera, achieving all-weather intrusion monitoring; (2) The authors propose a new multi-level fusion algorithm based on linkage and tracking to achieve intrusion target monitoring under adverse weather conditions; (3) The authors have conducted a large number of innovative simulation experiments to verify the effectiveness of the method proposed in this article.

This study focuses on the classification of targets with varying shapes using radar cross section (RCS), which is influenced by the target’s shape. This study aims to develop a robust classification method by considering an incident angle with minor random fluctuations and using a physical optics simulation to generate data sets.

The approach involves several supervised machine learning and classification methods, including traditional algorithms and a deep neural network classifier. It uses histogram-based definitions of the RCS for feature extraction, with an emphasis on resilience against noise in the RCS data. Data enrichment techniques are incorporated, including the use of noise-impacted histogram data sets.

The classification algorithms are extensively evaluated, highlighting their efficacy in feature extraction from RCS histograms. Among the studied algorithms, the K-nearest neighbour is found to be the most accurate of the traditional methods, but it is surpassed in accuracy by a deep learning network classifier. The results demonstrate the robustness of the feature extraction from the RCS histograms, motivated by mm-wave radar applications.

This study presents a novel approach to target classification that extends beyond traditional methods by integrating deep neural networks and focusing on histogram-based methodologies. It also incorporates data enrichment techniques to enhance the analysis, providing a comprehensive perspective for target detection using RCS.

The purpose of this paper is to present a deep-learning-based beamforming method for phased array weather radars, especially whose antenna arrays are equipped with large number of elements, for fast and accurate detection of weather observations.

The beamforming weights are computed by a convolutional neural network (CNN), which is trained with input–output pairs obtained from the Wiener solution.

To validate the robustness of the CNN-based beamformer, it is compared with the traditional beamforming methods, namely, Fourier (FR) beamforming and Capon beamforming. Moreover, the CNN is compared with a radial basis function neural network (RBFNN) which is a shallow type of neural network. It is shown that the CNN method has an excellent performance in radar signal simulations compared to the other methods. In addition to simulations, the robustness of the CNN beamformer is further validated by using real weather data collected by the phased array radar at Osaka University (PAR@OU) and compared to, besides the FR and RBFNN methods, the minimum mean square error beamforming method. It is shown that the CNN has the ability to rapidly and accurately detect the reflectivity of the PAR@OU with even less clutter level in comparison to the other methods.

Motivated by the inherit advantages of the CNN, this paper proposes the development of a CNN-based approach to the beamforming of PAR using both simulated and real data. In this paper, the CNN is trained on the optimum weights of Wiener solution. In simulations, it is applied on a large 32 × 32 planar phased array antenna. Moreover, it is operated on real data collected by the PAR@OU.

When it comes to discovering the leaders of the future, how can hiring organizations build a more sensitive talent radar to pick up signals of early-stage talent? What do upcoming leaders need to do to appear on that radar? What kind of search strategy is needed to find the exceptional candidate? Based on dozens of interviews with talent development specialists, we present 11 characteristics that emerge as keys to success. We present a case that illustrates why executive search is high stakes-game of responsible positions, and examine why talent alone is no guarantee of success.

An earlier form of this chapter by the author was published in Dutch in “Bestemming Boardroom: over zoeken en gevonden worden” (Boom, Amsterdam, 2018) and in English (online) by the Amrop Partnership (2021) as “Destination Boardroom 2: The Talent Radar.”

The aim of this paper is to analyse how technological innovations in performance measurement systems make it possible to overcome some of the challenges that public healthcare organizations face where management and control are concerned. The changes that could be applied to the performance measurement system of healthcare organisations were analysed together with an evaluation of the responses developed in order to achieve these changes.

The paper contains an in-depth case-study of a public university hospital which utilises an innovative information system.

The case-study highlights how technological innovations in performance measurement systems impact the management and monitoring information system in a public university hospital, through the implementation of a multidimensional management dashboard.

The limitation of this paper is that only one case-study is analysed, albeit in depth, while it would be interesting to consider more public university hospitals.

The paper highlights the fundamental role of middle management in change processes in the healthcare sector.

The case-study highlights how critical the active involvement of middle management is in performance measurement and management, and how this is achieved thanks to the adoption of a simple, clear method which ensures comprehensible communication of the objectives, as well as the measurement of performance by means of radar plots.

This study aims to learn the dynamic radar cross-section (RCS) of a deflection air brake.

The aircraft model with delta wing, V-shaped tail and blended wing body is designed, and high-precision unstructured grid technology is used to deal with the surface of air brake and fuselage. The calculation method based on multiple tracking and dynamic scattering is presented to calculate RCS.

The fuselage has a low scattering level, and the opening air brake will bring obvious dynamic RCS effects to itself and the whole machine. The average indicator of air brake RCS can be lower than –0.6 dBm² under the tail azimuth, while that of forward and lateral direction is lower. The mean RCS of fuselage is obviously higher than that of air brake, while the deflected air brake and its cabin can still provide strong scattering sources at some azimuths. When the air brake is opening, the change amplitude of the aircraft forward RCS can exceed 19.81 dBm².

This research has practical significance for the dynamic electromagnetic scattering analysis and stealth design of the air brake.

The calculation method for aircraft RCS considering air brake dynamic deflection has been established.

This paper aims to present the simulation, fabrication and testing of a novel ultra-wide band (UWB) band-pass filters (BPFs) with better transmission and rejection characteristics on a low-loss Taconic substrate and analyze using the coupled theory of resonators for UWB range covering L, S, C and X bands for radars, global positioning system (GPS) and satellite communication applications.

The filter is designed with a bent coupled transmission line on the top copper layer. Defected ground structures (DGSs) like complementary split ring resonators (CSRRs), V-shaped resonators, rectangular slots and quad circle slots (positioned inwards and outwards) are etched in the ground layer of the filter. The circular orientation of V-shaped resonators adds compactness when linearly placed. By arranging the quad circle slots outwards and inwards at the corner and core of the ground plane, respectively, two filters (Filters I and II) are designed, fabricated and measured. These two filters feature a quasi-elliptic response with transmission zeros (TZs) on either side of the bandpass response, making it highly selective and reflection poles (RPs), resulting in a low-loss filter response. The transmission line model and coupled line theory are implemented to analyze the proposed filters.

Two filters by placing the quad circle slots outwards (Filter I) and inwards (Filter II) were designed, fabricated and tested. The fabricated model (Filter I) provides transmission with a maximum insertion loss of 2.65 dB from 1.5 GHz to 9.2 GHz. Four TZs and five RPs are observed in the frequency response. The lower and upper stopband band width (BW) of the measured Filter I are 1.2 GHz and 5.5 GHz of upper stopband BW with rejection level greater than 10 dB, respectively. Filter II (inward quad circle slots) operates from 1.4 GHz to 9.05 GHz with 1.65 dB maximum insertion loss inside the passband with four TZs and four RPs, which, in turn, enhances the filter characteristics in terms of selectivity, flatness and stopband. Moreover, 1 GHz BW of lower and upper stopbands are observed. Thus, the fabricated filters (Filters I and II) are therefore evaluated, and the outcomes show good agreement with the electromagnetic simulation response.

The limitation of this work is the back radiation caused by DGS, which can be eradicated by placing the filter in the cavity and retaining its performance.

The proposed UWB BPFs with novel resonators find their role in the UWB range covering L, S, C and X bands for radars, GPS and satellite communication applications.

To the best of the authors’ knowledge, for the first time, the authors develop a compact UWB BPFs (Filters I and II) with BW greater than 7.5 GHz by combining reformed coupled lines and DGS resonators (CSRRs, V-shaped resonators [modified hairpin resonators], rectangular slots and quad circle slots [inwards and outwards]) for radars, GPS and satellite communication applications.

The aim of this study is to determine the fracture behavior of wool felt and fabric based epoxy composites and their responses to electromagnetic waves.

Notched and unnotched tensile tests of composites made of wool only and hybridized with a glass fiber layer were carried out, and fracture behavior and toughness at macro scale were determined. They were exposed to electromagnetic waves between 8 and 18 GHz frequencies using two horn antennas.

The keratin and lignin layer on the surface of the wool felt caused lower values to be obtained compared to the mechanical values given by pure epoxy. However, the use of wool felt in the symmetry layer of the laminated composite material provided higher mechanical values than the composite with glass fiber in the symmetry layer due to the mechanical interlocking it created. The use of wool in fabric form resulted in an increase in the modulus of elasticity, but no change in fracture toughness was observed. As a result of the electromagnetic analysis, it was also seen in the electromagnetic analysis that the transmittance of the materials was high, and the reflectance was low throughout the applied frequency range. Hence, it was concluded that all of the manufactured materials could be used as radome material over a wide band.

Sheep wool is an easy-to-supply and low-cost material. In this paper, it is presented that sheep wool can be evaluated as a biocomposite material and used for radome applications.

The combined evaluation of felt and fabric forms of a natural and inexpensive reinforcing element such as sheep wool and the combined evaluation of fracture mechanics and electromagnetic absorption properties will contribute to the evaluation of biocomposites in aviation.

The purpose of this paper is to systematically review the history and current state of lesson study (LS) in Germany. In particular, this paper describes the development of LS over time and its stakeholders.

Conducting a systematic literature review, we searched three scientific databases and Google Scholar, examined 806 results and included 50 articles in our final sample, which we analyzed systematically.

The spread of LS in Germany can be divided into three phases, characterized by their own LS projects as well as their own ways of understanding LS. Although interest in LS has increased significantly in recent years, it is only present at a small number of schools and universities in Germany if compared internationally. Furthermore, this paper identifies the so-called learning activity curves as a tool frequently used for observation and reflection that appears to be unknown outside German-speaking countries.

This paper may act as an outline for countries without large-scale LS projects and with limited support from policymakers. The experience from Germany demonstrates the outcomes and challenges that can arise in such a situation and shows how unique LS features and proceedings have emerged.

Nowadays, textiles play a striking role in various medical applications. Compression bandages are the most essential medical fabrics that help treat venous flow and edema. This study aims to investigate the characteristics of different woven compressive bandage structures produced using compact cotton and cotton/lycra.

Four samples were weaved by matt-plain2/2, twill2/2, stripe-stain4 and mock-leno structures. Several properties were tested that related to structural performance. Tensile strength, elastic and sub-bandage pressure are considered the main functional properties. Three different analysis tools were performed: chart-diagram, one-factor ANOVA and radar chart area.

The woven structures critically affected the performance of woven compression bandage samples as well as their classifications.

The woven structures critically affected the performance of woven compression bandage samples as well as their classifications.