Miracle-dz/UniFAR-FTUs huggingface dataset:
High-Isolation Dual-band Shared Aperture Binomial Antenna Array for Airborne Synthetic Aperture Radar Applications

The article presents a two-bands (X/Ku) binomial antenna array with linear polarizations for a shared aperture antenna. The proposed standard linear-polarized antenna array has several advantages low cost, low profile, high isolation, and low cross-polarization. The amplitude distributions of dualdifferent bands of binomial array antenna are creatively linked in the same aperture and resonant at different frequencies. Because of the compact of high isolation and low polarized, binomial arrays are presented as X/Ku-band elements, and the size of the designed antenna was 210×60×0. 8mm3. The results are provided by using CST Microwave Studio Simulator. In this method, series feed center-fed and open stub with reduced polarization levels are simulated for two different operational frequencies (9.3GHz, and 13.265GHZ) at isolation between port-1 and 2 is -57, The bandwidth of 0.088%(X-band) and 1.79%(Ku-Band), Return Loss for 25dB/-15.7dB and Proposed antenna gains are X/KU 13.7dBi/13.4 dBi. The antenna provides high isolation and low cross-polarization above 25 dB. A proposed tapering technique for an antenna X/Ka-band linear-polarized antenna array has been described, which may be helpful in Synthetic Aperture Radar applications
Software Defined Underwater Communications: an Experimental Platform for Research

Underwater Acoustic Networks have become widely adopted in many marine and underwater contexts thanks to the increased availability of devices and technologies over the years. Even though the number of Commercial Off-the-Shelf devices has increased in the last decade, underwater technology still remains a very expensive asset to acquire. Moreover, the technology is almost always licensed and inaccessible to the user, to protect intellectual property and industrial patents. This last point is often a problem for the researchers that do not intend to make profit from algorithms or patented ideas but instead leverage on the existing technology to install and test their own solutions to advance the state of the art. Also, researchers very often resort to simulation and emulation to test and evaluate their algorithms: this approach not only guarantees freedom of implementation but also avoids the issues of organizing a field trial in the ocean or at sea, and is definitely cheaper. However, to prove the effectiveness of the proposed solutions in real environments, simulation may not be sufficient. In this paper we present a complete tool for testing and evaluating the full protocol stack, from application to physical layer, with both simulation and real field experimentation, that integrates the open source DESERT Underwater framework and a low cost software-defined acoustic modem.
Network-wide Traffic State Forecast Using Discrete Wavelet Transform and Deep Learning

Traffic state prediction models are a crucial element with many applications in intelligent transportation systems. Short-term network-wide modeling of traffic states is a challenging task due to the existence of inherent characteristics such as nonlinearity, periodicity and stochasticity in the traffic state time series. This issue was responded by the evolution of advanced machine learning algorithms, e.g. deep learning. Deep neural networks can cope with high dimensionality, and also, are capable of extracting nonlinearity, comovement patterns, and spatiotemporal interdependencies between the traffic state variables from different locations. Nevertheless, they cannot completely capture the location-specific features of traffic information. Therefore, we propose the Discrete Haar Wavelet Transform (DHWT) as a preprocessing scheme prior to Multilayer Perceptron (MLP) neural networks for one-hour ahead traffic state prediction. DHWT can help MLP to simultaneously learn the network-wide comovement patterns through the trend component time series, and seize the significant characteristics of each unique detector efficiently via the noise component. The results on 20 sensors in Paris indicated that the hybrid DHWTMLP model with a two-level down decomposition improves the Mean Squared Error (MSE) of a non-preprocessed MLP by 33.73% and 17.58 %, for the six-month and three-month data, respectively. However, the proposed model does not perform well over the one-month period compared to the MLP model. Therefore, it may be helpful to use lower wavelet decomposition levels (higher orders) when dealing with relatively small traffic datasets.
Comparison of decision support models -- a recruitment case study as a multiclass classification problem with limited data

We present a comparative case study of machine learning models, evaluating their efficiency in a practical task of multiclass classification of samples being submissions to a recruitment survey and assigning them scores denoting the match level for a given candidate to a given workgroup (committee) in the AGH Students’ Council. This research is based on the Council’s recruitment applications that carried candidates’ responses to a set of 10 hypothetical Council member activity scenarios, where they were to choose one of four given solutions to the problems. The data was collected from a web quiz in 2020, validated on a voluntary insider control group’s responses to these questions and finally the best-performing model was evaluated in practice in the 2021’s recruitment inside an in-browser adventure minigame. This work provides insight into how models ranging from classical methods to deep learning perform in a very specific not yet well-explored in literature, practical non-linear problem that is dependent on individual features of the participants, with the data volume being very limited due to a restricted population of candidates. This information may provide a starting point for applications of machine learning in decision support systems in recruitment processes.
A fast algorithm for reconstruction-based superresolution and evaluation of its accuracy

A superresolution process produces a high-resolution image from a set of low-resolution images. Reconstructionbased algorithms to produce the high-resolution image which minimizes the difference between observed images and images estimated from the high-resolution image with a camera model have been developed. The reconstructionbased algorithm requires iterative calculation and has a large calculation cost because reconstruction-based superresolution is a large-scale problem. In this paper, a fast algorithm for reconstruction-based superresolution is proposed. The proposed algorithm reduces the number of observed pixel value estimations from the high-resolution image, using an average of pixel values in a divided region. The effect of our proposed algorithm is demonstrated with synthetic images and real images. The results show that the proposed algorithm is about 1.4 to 8.5 times faster than conventional algorithms. © 2007 Wiley Periodicals, Inc. Syst Comp Jpn, 38(7): 44–52, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.20662
Automated Lineage Inference among Malware Families

To effectively expand illegal proceeds, current malware has exhibited a trend of modular derivation, resulting in a continuous reduction in the time cycle from design to completion of a new family. The rapid evolution of malware families makes lineage analysis urgent for security practitioners. However, the techniques are still in the exploratory stage; their applicability is limited due to the lack of automated methods. As time passes and malware evolves, the insights gained from such methods will become less applicable to new situations, and their reference value will be greatly reduced. In this paper, we propose an automated approach to analyzing the lineage relationship among malware families and apply our approach to a Windows malware dataset of more than 57,000 samples. The experimental results prove that our approach can effectively extract the core functions of samples and reasonably infer the association relationship among different families.
Assessment of Airborne Light Detection and Ranging (LiDAR) for use in common forest engineering geomatic applications

approved: __________________________________________________________ Michael G. Wing Airborne Light Detection and Ranging (LiDAR) has become a popular remote sensing technology to create digital terrain models and provide forest inventory information. However, little research has been done to investigate the accuracy of using airborne LiDAR to perform measurement tasks common to Forest Engineering. This thesis contains two manuscripts investigating different measurement scenarios. The first manuscript examines the use of airborne LiDAR to measure existing forest roads in support of a road assessment under four different canopy conditions. It was found that along existing centerlines the LiDAR data had a vertical RMSE of 0.28 m and a horizontal RMSE of 1.21 m. Road grades were estimated to within 1% slope of the value measured in the field and horizontal curve radii were estimated with an average absolute error of 3.17 m. The results suggest that airborne LiDAR is an acceptable method to measure forest road grade, but some caution should be used in measuring horizontal curve radii, particularly on sharp curves. The second manuscript compares profile corridor measurements using airborne LiDAR-derived elevations across different forest canopy types and terrain slopes ranging from 37 to 49%. Both LiDAR-derived DEM and raw LiDAR point elevations were compared to field data. The DEM elevations had an average RMSE error of 0.43 m across all canopy types compared to the field data, while the nearest LiDAR point had an average RMSE of 0.49 m compared to the field data. A skyline payload analysis suggested that profiles based on the DEM outperformed profiles based on nearest point elevations by 5% on average when compared to the field measured profiles. Results suggest that a forest engineer should consider using the DEM value rather than the nearest LiDAR point elevation for terrain elevations at discrete locations, particularly when forest canopy occludes locations of interest. ©Copyright by Michael B. Craven June 10, 2011
Creative activity support by discovering effective combinations

Creative activities based on combinations are now being carried on everywhere in the world. Whether or not the creative activity succeeds depends on the combinations used in it. Since there are tremendous numbers of candidate combinations, it is impossible to decide at a glance which should be used. Thus, there must be a method of efficiently discovering combinations which are effective in making creative activity a success. This paper proposes a method of discovering combinations that is effective in supporting creative activity. In the proposed method, the originality of each combination and the novelty perceived by users are estimated from the number of hits on Web pages containing the keywords in question, and the effectiveness of the combinations is judged. © 2007 Wiley Periodicals, Inc. Syst Comp Jpn, 38(12): 99–111, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.20392
Floods: Physical Processes and Human Impacts

THE FLOOD HAZARD IN CONTEXT. Floods: Physical Events and Natural Hazards. Impacts and Interpretations of Flood Hazard. PROCESSES OF FLOODING. River Floods: Geophysical Processes. River Floods: Spatial Characteristics. Coastal Floods. Flood Estimation. RESPONSES TO THE FLOOD HAZARD. Flood Defence. Flood Forecasting and Warning. Mitigating and Managing Flood Losses. Outlook. Appendix. References. Index.
Speech Emotion Recognition Using Multi-task Learning and Sentence-level Embedding Loss

It is necessary but challenging to make speech emotion recognition (SER) sufficiently accurate, since the generation and expression of human emotion are so complicated. In this paper, we propose an end-to-end model with a multi-task learning framework and a novel embedding loss on the SER task. By multi-task learning, SER task and automatic speech recognition (ASR) task are combined with a shared encoder, which can capture the intrinsic relation of different tasks and make use of the deeper features during training. Furthermore, we introduce an embedding loss to the model to keep sentence level consistency. Experiments on IEMOCAP and Emotional Speech Database (ESD) show that the multi-task learning framework and embedding loss contribute a lot to the model performance, which improves the weighted accuracy by an absolute of 16.2% to our baseline model.
ReRobo Walker: Robotic Walker with Fall Detection and Active Safety

In recent years, Chinese society has become increasingly ageing while the fertility rate continues to decline. This situation has led to a growing public demand for rehabilitation devices such as walking aids. A novel intelligent robotic walker named ReRobo Walker is proposed which can assist groups of elderly people with dysfunctional legs with rehabilitation training and indoor and outdoor walking. We design robust mechanical structures for robotic walker, install special 3D force sensor, 2D LIDAR and other sensors, and design new algorithms to enable intelligent functionality while guaranteeing the safety of robotic walker. (1) Real-time monitoring of the user’s physical status, such as falls, through laser range sensors and 3D force sensor; (2) Modelling of the scene through 2D LIDAR for path planning, obstacle avoidance and navigation functions; (3) Precise control through LADRC-based algorithm for uphill assistance, downhill control and prevention of sharp shifts of the robotic walker. Experiment results demonstrate the solid mechanical structure, stable reliability and the effectiveness of intelligent control algorithms of the intelligent robotic walker.
Relating Best Practices to Standardization in Ocean Science

Over the past decade, the Ocean Best Practices System, hosted and maintained by the International Oceanographic Data and Information Exchange of UNESCO’s Intergovernmental Oceanographic Commission, has grown to become a trusted and stable repository for all types of ocean Best Practices documentation. Given the nature of the information it contains, the repository embodies a unique resource base for supporting initiatives aimed at strengthening standardization in Ocean Science. Based on this consideration, the Ocean Best Practices System is forming a new task team to explore and evaluate the potential role that the comprehensive Best Practice information it secures could play in identifying and prioritizing processes for furthering this objective. Particular care is being taken to keep the work open and transparent through constant community engagement and by linking with international bodies/organizations dealing with measurement.
A geometric measurement system using a robot as handling system and reference system

Collaborating robots are used at production processes to interact with workers and they don’t need separation by protective devices. These robots could be used for in-place geometric measurements through some adjustments. This paper deals with the advantages of highly accurate geometric measurements using a cobot, steps of adjustments are described and some first startup measurements are presented.
Independent Tether Management Nodes for Subsea Vehicles in Complex Fields

This paper presents a Tether Multipoint Management System (TMMS) for a Resident Remotely Operated Vehicle (ROV) in offshore operations. Operating close to structure or seabed. Boulders etc tether management is critical to ensure the safety and effectiveness of operations without tether entanglement. The proposed TMMS is composed of one or more Independent Tether Management Nodes (ITMN) enabling the ROV to move freely and autonomously around offshore structures while minimizing the risk of tether entanglement. The ITMN can use a combination of active thrusters (axial, lateral, and vertical) and passive (buoyancy and fin) control to achieve the necessary degrees of freedom and an onboard battery for power. The proposed system expands the operational capability of the ROV, allowing it to perform tasks not possible beforehand, saving time and increasing efficiency.
EM Design and Analysis of FSS-based Composite Broadband Radar Absorbing Structure

EM design and performance analysis of FSS-based composite broadband radar absorbing structure (RAS) is presented in this paper. In this design hybrid FSS unit is used where square patch and cross dipole are arranged in the diagonal direction. The square patch resonates at lower frequency side while cross dipole resonates at higher frequency side that leads to broadband characteristics. The EM analysis of proposed FSS-RAS is carried out using commercial HFSS software. The total thickness of FSS-RAS is optimized to be 3.8 mm for better EM absorption characteristics. The proposed FSS-RAS is observed to exhibits broadband absorption characteristics from 6 GHz to 21.7 GHz w.r. t. -10 dB reflection loss. Moreover, the EM characteristics is found to be polarization independent up to 50° incidence angle. Such FSS-RAS can potentially be used over leading wing edge of aircraft to reduce its radar signature.
A compact C-shaped Stub Loaded Quad-band monopole antenna for Wireless applications

The proposed paper presents a compact quad-band microstrip patch monopole antenna with a tunable capability. The proposed monopole antenna is formed by introducing the three C-shaped stubs of different lengths with a rectangular ring. The antenna uses an FR-4 substrate with a thickness of 0.5 mm. The proposed antenna is fed by a 50Ω CPW line and has a compact size of 20×21 mm2. The antenna operates at 2.58 GHz, 3.47 GHz, 3.66 GHz, and 4.07 GHz frequencies. The key parameters such as reflection coefficient, peak gain, and antenna radiation pattern are analyzed using ANSYS electronic desktop HFSS software.
Control of a point absorber wave energy converter in extreme wave conditions using a deep learning model in WEC-Sim

The survivability of wave energy converters (WECs) is one of the challenges that have a direct influence on their cost. To protect the WEC from the impact of extreme waves, it is often to over-dimension the components or adopt survivability modes e.g. by submerging or lifting the WEC if it is applicable. Here, a control strategy for adjusting the system damping is developed based on deep neural networks (DNN) to minimize the line (mooring) force exerted on a 1:30 scaled WEC. This DNN model is then implemented in a control system of a numerical WEC-Sim model to find the optimal power take-off (PTO) damping for every zero up-crossing episode of surface elevation which minimizes the peak line force. The WEC-Sim model was calibrated based on a 1:30 scaled wave tank experiment that was designed to investigate the WEC response in extreme sea states with a 50-year return period. It is shown that this survival strategy reduces the peak forces when compared with the response of a system that has been set to a constant PTO damping for the entire duration of the sea state.
On-Board Internal RF Calibration Electronics for Space-borne SAR

This paper presents the design and measured results of On-board Internal RF Calibration Electronics comprising of a low power dissipation Calibration Switch Matrix realized using hermetically sealed MMIC based Single Pole Double Throw (SPDT) and Single Pole Single Throw (SPST) switches with coplanar waveguide with lower ground plane (CPWG) interconnects and calibration signal distribution network realized using RF power dividers for X-Band Synthetic Aperture Radar (SAR). Calibration signal routing functionality for all antenna beam outputs, individual High Power Amplifier (HPA) outputs, individual Front-end Low Noise Amplifiers (LNA) of all antenna beams as well as the chirp (replica) has been realized by configuring a 3x2 Calibration Switch Matrix comprising of 2 inputs, 1 output and 1 bidirectional port. This multi-facet on board calibration scheme is required in SAR payloads to know the actual differential phase and amplitude variations across the transmit and receive modules, the actual imbalances of the antenna beams and having a reference chirp (replica) data required for pulse compression. The main and redundant switch matrix units are stacked with its respective Electronic Power Conditioning (EPC) unit and cross patching power dividers in a three-tier stack. Excellent isolation between desired and undesired signal along all paths has been achieved with the switches consuming a power of only 160mW. A low power dissipation, high isolation X-Band switch matrix, required for On-board Internal RF calibration electronics, has been designed, realized and successfully delivered for three satellite constellation of 8-beam reflector based SAR.
Prescribed-Time Stabilization for a Class of Switched Nonholonomic Systems

In this paper, the problem of prescribed-time stabilization (PTS) is studied for a class of nonholonomic systems (NSs) with switched chain structures. By suitably introducing the time-varying function into the virtual (actual) controllers, a non-scaling transformation design scheme for state feedback is developed, which forces the states of the closed-loop system (CLS) to zero in any prescribed finite time. Finally, simulation results are given to confirm the efficacy of the proposed method.
Energy-Efficient Routing Protocol Based on Data Dissemination for Underwater Wireless Sensor Network

Underwater wireless sensor network (UWSN) has attracted much research interest in recent years, especially suitable routing protocols. In this paper, we design a multi-hop energy-efficient routing protocol based on data distribution. Specifically, we consider the actual underwater three-dimensional model, which results in severe energy consumption. During data transmission, relay nodes will serve for data distribution for the purpose of energy efficiency, where the nodes farther away from the surface sink node undertake fewer data forwarding tasks. The amount of data transmitted by each relay node is quantitatively related to the distance. Meanwhile, the TDMA MAC protocol is reasonably applied to the acoustic link. The simulations demonstrate that our routing protocol outperforms the reference algorithms in terms of network lifetime and energy consumption balance.