esa-sceva/satcom-chunk-collection huggingface dataset:
## A UGV Platform
### Data Transmission and Recording  
Data acquisition and transmission take place in parallel using several channels. Thermal and RGB images are registered locally within the board computer. Additionally, together with the vision, the robot position relative to the localization system and time information is recorded, which allows us to synchronize two independent camera feeds, as well as identify the event location such as a fault. To confirm the correctness of the view, it is possible to see the camera feed via WiFi (for example using remote desktop). Downloading of the data takes place after the mission ends.  
The structure of the system is prepared in a way that it is possible to conduct a mission automatically; however, in the early stage of the development the robot works in teleoperation mode. Further publications will describe more results related to autonomous applications.  
Figure 16: An algorithm of hot area detection.
# Collision-Aware Routing Using Multi-Objective Seagull Optimization Algorithm for WSN-Based IoT
## 7 Conclusions  
Advancements in computer technology have contributed to the growth of WSNs, which sense the requisite parameters at any time. The WSN-based IoT systems are gaining huge attention in recent times. During point-to-point transmission, these systems suffer from restricted bandwidth, low power, and limited resources. Collecting the data is a familiar method for alleviating the above-mentioned problem, but the key problem in sensor networks is how to process the collected data efficiently. Therefore, in this paper, collision-aware routing using a multi-objective SOA (CAR-MOSOA) is proposed to transmit the alert messages using the IoT devices to the respective destination with a significantly reduced delay. The proposed works defining the role of IoT in WSN are analyzed and then the various data aggregation approaches are presented and compared with previous works. The data aggregation techniques focus on energy conservation, lifetime enhancement, better QoS, and high-level security of the network. The overall simulation clearly shows that the proposed CAR-MOSOA achieved better results by minimizing the energy consumption and end-to-end delay by up to 25% and 34%, respectively. Moreover, the network lifetime and PDR increased by up to 5.96% and 3.15%, respectively, when compared to the TSGWO method. In the future, this research will be extended to use hybrid optimization techniques to improve the performance of the network.  
The paper investigation, resource collection, data curation, writing--original draft preparation, writing--review and editing, and visualization were done by [PERSON] and [PERSON]. The paper conceptualization and software were handled by [PERSON] The validation, formal analysis, methodology, supervision, project administration, and funding acquisition of the version to be published were managed by A.S. and P.B.D. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
No new data were created or analyzed in this study. Data sharing is not applicable to this article.  
The authors declare no conflict of interest.
# TransECA-Net: A Transformer-Based Model for Encrypted Traffic Classification
## 2 Related Work
### Port-Based Methods  
The early classification of network traffic predominantly hinged on port numbers and protocol analysis. In an era when network applications were limited and relatively static, port-based approaches demonstrated efficacy. In 2009, [PERSON] et al. [15] introduced a technique for classifying application traffic leveraging fixed IP-port information, which involved matching packet headers with the aggregated fixed IP-port data. Nevertheless, as network technologies have evolved, malicious actors have developed methods to obscure their true traffic types by modifying traffic ports, thereby circumventing detection mechanisms that rely on fixed port classifications. Furthermore, port-based classification methodologies primarily rely on the identification of port number characteristics, neglecting other significant attributes such as packet content and protocol headers. Consequently, the classification capacity of this approach is inherently constrained and fails to fully capitalize on the extensive information embedded within network traffic.
## 5 Numerical Simulation Results and Discussion
### Practical Test 1: Imbalanced Vertical Shift Response  
From the FFT characteristics (Figure 15b), it is evident that the resonant frequency is higher than in the case of the imbalanced drill string operating in water in Figure 15a. The experimental results demonstrate that, during start-up, the lateral trajectory of the drill string increases gradually, and its circular orbit consists of mixing two harmonic paths of different frequencies (Figures 15a and 16a). The orbital path rotates at a considerably lower amplitude (note the different magnitudes in the X- and Y-axes in the figures after immersion) as shown in Figures 15b and 16b.  
For the experiment presented, the drill string rotates in the air, and for the fluid, at a speed of approximately 1600 rpm with an imbalanced mass, the progressive excitation leads to rubbing contact. Due to the constraint on the axial displacement, measurement probes (Figure 6d) to detect the behavior of the drill string downhole were used for the actual drill string and to extract the characteristics when some unwanted vibration occurred in the fluid medium. The lateral vibrations of an imbalanced swirling drill string at critical velocities and influenced by fluid forces were measured, and the impulse characteristics were then extracted and plotted as shown in Figures 17 and 18.  
Figure 16: Experimental frequency response of the imbalanced rotor (**a**) without water and (**b**) with water.  
Figure 15: Experimental orbit response of the imbalanced drill string in fluid (**a**) without water and (**b**) with water.
## 1 Introduction
Experimental results further validate the effectiveness of ZWNet, as evidenced by the normalized coefficient of the zero-watermark consistently exceeding 0.97 for robustness and the Hamming distance between watermarks with the same copyright and different images surpassing 88 for discriminability. The contributions of this paper can be summarized as follows:  
(1) Introduction of a novel approach that combines ConvNeXt and LK-PAN to enhance feature extraction, effectively addressing both global context and local features. (2) Transformation of the problem of improving watermark performance into a classification task, leveraging the common framework provided by deep learning. (3) ZWNet exhibits notable discriminability, ensuring that the generated zero-watermark is distinct enough to differentiate between different images sharing the same copyright. This capability addresses the challenge of zero-watermark confusion. The structure of this paper is organized as follows: Section 2 provides a concise background on zero-watermarking, ConvNeXt, and LK-PAN. Section 3 introduces the proposed zero-watermarking scheme, \"ZWNet\". Section 4 delves into the presentation of experimental results and subsequent discussion. Finally, Section 5 presents the concluding remarks.
# Transparent Redirections in Content Delivery Networks
## 2 State of the Art
### CDN Redirections
#### 2.2.3 Transport Layer Request Routing  
Transport-layer request routing requires service awareness and support from the network. Transport-layer request routers use information in the transport-layer headers (optionally application layer details too) to determine to which CDN surrogate hand off the session, which proceeds to serve the requested content [8]. Such handoff can be achieved by migrating the TCP session from the request router to the surrogate server or by achieving triangular routing, where the requests go from the client towards the request router, which forwards the requests to the surrogate server. The surrogate server proceeds to serve the content directly, while the IP address and port numbers are re-written by the network (depicted in Figure 3) [10]. This article focuses on these type of redirections. Some existing solutions are presented in the next section.  
Figure 3: Triangular routing.  
Figure 2: Application layer redirection.
# Integrating a Path Planner and an Adaptive Motion Controller for Navigation in Dynamic Environments
## 3 The Methodology
### Global Path Planner Based on JPS+ (P)  
Figure 3a-c shows the offline work of the path planner, which includes constructing warning areas and identifying subgoals by preprocessing. Without the warning areas computed based on distance maps, the subgoals would be too close to the obstacles for moving robots, which increase the probabilities of colliding with walls.  
Figure 3: A graphical representation of how Jump Point Search+ (Prune) (JPS+ (P)) preprocesses an initially known grid-based map and what the paths that it plans look like. (**a**) An original map in which the white and black cells are unblocked and blocked locations, respectively. (**b**) Gray cells denote warning areas. (**c**) Jump points are marked as red. (**d**) Green lines denote an optimal path planned by JPS+ (P).  
During the process of constructing warning areas, the dynamic brushfire algorithm [31] is used to build the Euclidean distance map (EDM) based on the original map. The minimum distance between robots and obstacles is limited by the physical radius of robots; thus, a user-defined safety distance is required to increase insurance for robots that carry out important tasks. Therefore, the size of warning areas is determined by the above two factors (Figure 3b).  
In the JPS family, jump points are the intermediate points that are necessary to travel through for at least one optimal path [14]. To put it simply, JPS and JPS+ call locations where a cardinal search can branch itself to wider areas due to obstacle disappearance in the incoming direction straight jump points. For example, in Figure 3c, an eastern search from A3 wraps around obstacles at C3, and then broadens itself to the southeastern areas. Besides straight nodes, they identify diagonal jump points linking two straight ones where the incoming diagonal search from the first can turn cardinally to reach the second. JPS+ improves JPS through exploiting diagonal-first ordering in the offline phase, and storing for each traversable cell the distance to the nearest jump point or obstacle that can be reached in every cardinal or diagonal direction. More details can be found in [14; 32].  
This paper applies JPS+ (P), which is an enhanced version of JPS+ with an intermediate pruning trick; thereby, the optimal path in Figure 3d will not generate and expand the diagonal jump point H8. JPS+ (P) requires the same preprocessing overheads to JPS+, but has stronger online efficiency.  
To sum up, JPS+ (P)--which we borrow from [32]--has obvious advantages over other high-level planners of hierarchical methods in the literature [24; 25; 26], in terms of its low precomputation costs and outstanding online performance. Moreover, it serves as an ideal for the location distribution of jump points, providing a DRL-based controller with meaningful subgoals that can completely throw the problem of local minima out of consideration.
###### Abstract  
To achieve long-distance underwater optical wireless communication, a single photon detector with single photon limit sensitivity is used to detect the optical signal at the receiver. The communication signal is extracted from the discrete single photon pulses output from the detector. Due to fluctuation of photon flux and quantum efficiency of photon detection, long-distance underwater optical wireless communication has the characteristics that the link is easily interrupted, the bit error rate is high, and the burst error is large. To achieve reliable video transmission, a joint source-channel coding scheme based on residual distributed compressive video sensing is proposed for the underwater photon counting communication system. Signal extraction from single photon pulses, data frame and data verification are specifically designed. This scheme greatly reduces the amount of data at the transmitter, transfers the computational complexity to the decoder in receiver, and enhances anti-channel error ability. The experimental results show that, when the baud rate was 100 kbps and the average number of photon pulses per bit was 20, the bit error rate (BER) was 0.0421 and video frame could still be restored clearly.  
photon-counting; underwater optical wireless communication; distributed compressive video sensing +
Footnote †: journal: Sensors
# Cartesian Aerial Manipulator with Compliant Arm
## 1 Introduction
### Contribution of This Work  
The main contribution of this paper is the design, development and experimental validation of a new morphology of aerial manipulation robot consisting of a hexa-rotor platform integrating a 2-DOF (degree of freedom) Cartesian base (XY-axes) that carries a 1-DOF compliant joint arm equipped with a gripper and a deflection-based force-torque sensor. Figure 1 shows a picture of the prototype. The proposed morphology is intended to improve the positioning accuracy of the end effector while reducing the inertia, torque and weight of the actuators, since the Cartesian base supports most of the weight of the robotic manipulator (0.85 kg weight, 1 m reach, and 10 cm/s speed). The elastic deflection sensors integrated in the compliant joint and in the fore-arm link are used to estimate and monitor the force (XZ-axes) and torque (pitch) exerted by the manipulator over the aerial platform. This allows the realization of a number of tasks such as sensor installation with contact force control, force monitoring in grabbing situations, or object grasping and retrieval. The kinematic and dynamic models of the aerial manipulator are derived, while analyzing in more detail the error propagation at the end effector from the Jacobian, comparing the proposed morphology with respect to that of a revolute-joint arm in terms of positioning accuracy, reach, and workspace. This paper also proposes a force-position control scheme for the aerial robot that takes into account the wrench estimation provided by the arm.  
Experimental results conducted in test-bench as well as indoor/outdoor flight tests validate the functionalities and capabilities of the developed Cartesian aerial robot.  
The rest of the paper is organized as follows. Section 2 presents the motivation for and describes the prototype of a Cartesian aerial manipulator with compliant joint arm. Section 3 presents the kinematic and dynamic models of the aerial robot, analyzing and comparing the features of the Cartesian manipulator with respect to a revolute-joint arm. Section 4 covers the control of the aerial robot, the experimental results are shown in Section 5, and the conclusions in Section 6.
_Article_  
Assessment of Accidental Torsion in Building Structures Using Static and Dynamic Analysis Procedures  
**[PERSON] 1,*()** and [PERSON] 2()  
1 College of Engineering, Abu Dhabi University, Abu Dhabi PO Box 59911, UAE  
2 UNii Engineering Consultancy, Abu Dhabi PO Box 47378, UAE; [EMAIL_ADDRESS]m  
* Correspondence: [PERSON]S]  
Received: 6 July 2020; Accepted: 7 August 2020; Published: 9 August 2020  
**Featured Application: This article presents a model that overcomes the discrepancies between the accidental torsion response obtained using static and dynamic analysis methods. The frequency ratios for which static analysis overestimates torsional response were identified. Similarly, the frequency ratios for which static analysis underestimates torsional response were also identified.**  
This article presents the findings of a study on assessment of the increase in building's response due to accidental torsion when subjected to seismic forces. Critical stiffness and geometrical parameters that define buildings torsional response are examined including: (1) the ratio, \(\Omega\), between uncoupled torsional frequency \(\omega_{\theta}\) to uncoupled translation frequencies in the direction of ground motion \(\omega_{x}\) or \(\omega_{y}\), (2) floor plan aspect ratio, \(b\!r\), which is a function of the floor dimension and radius of gyration. The increased response is assessed on symmetric multi-storey buildings using both static and dynamic analysis methods specified by ASCE-7 and considering parameters affecting the torsional response. It was concluded that static and dynamic analysis procedures predict different accidental torsion responses. Static analysis based on the Equivalent Lateral Force (_ELF_) method predicts more conservative accidental torsions responses for flexible structures with \(\Omega<0.7\)-\(0.80\), while the responses are less conservative for stiffer buildings. The conservativism in static analysis method is attributed to the response amplification factor, _Ax_. Floor plans and their lateral support system having frequency ratio \(\Omega=1\) will also have a torsional radius equal to radius of gyration, and will experience drop in torsional response relative to more torsionally flexible buildings. This article presents a procedure to overcome the shortcomings of static and dynamic analysis procedures in terms of estimating accidental torsion response of symmetric building structures.  
**Keywords: Torsional irregularity; accidental torsion; translation frequency; torsional frequency; frequency ratio; ground motion**
## 4 Carols Airborne Data Analysis
### Methods for Qualification of CAROLS Data
#### 4.1.1 TRAP Software Tool  
The TRAP software allows the various contributions affecting the L-band brightness temperatures to be simulated. It uses the physical modeling of celestial, atmospheric and oceanic signals as for the processing of SMOS salinity data [17]: the atmospheric emissivity and absorption model from [PERSON] _et al._[18]; the sea surface emissivity for a flat sea surface from Klein and Swift [19]; in our analysis, by default, the contribution to emissivity of the sea surface roughness is estimated using a two-scale model based on the Durden and [PERSON] x2 wave spectrum [20] (2 scale/DV2); we also tested the rough surface emissivity simulated by a small slope approximation model, and the [PERSON] _et al._[21] wave spectrum (SSA/Kudr.). Scattering of galactic noise by the ocean surface has been simulated by [PERSON] _et al._[22]. The atmospheric pressure and relative humidity data needed to run the atmospheric model were taken either from the Gascogne buoy (45.2\({}^{\circ}\)N, 5\({}^{\circ}\)W), or from the European Center for Medium range Weather Forecast (ECMWF); the wind speed needed to estimate the impact of roughness on the sea surface emissivity, and on the sea surface scattering of atmospheric and galactic signals, was taken from QuikSCAT measurements recorded within less than two hours of the CAROLS flights, or from the Gascogne buoy measurements. The sea surface salinity and temperature values needed to simulate the sea surface emissivity were derived from the ship and buoy measurements. Our primary goal was to validate the instrument. Thus, in order to achieve a clear separation between the analyses of data recorded by each antenna port, we chose to simulate the antenna temperatures in the polarization reference system defined by the antenna framework. This allowed us to avoid mixing the measurements made by different antenna ports, which would be needed to reconstruct horizontally and vertically polarized signals. TRAP takes on account aircraft maneuvers to consider mixing between polarizations, for each antenna port. Integration of the simulated signal over the gain of the antenna pattern was achieved using the antenna diagram measured in the laboratory (very close to a Potter horn).
# Modified Generalized Feistel Network Block Cipher for the Internet of Things
## 2 Related Work
PICCOLO employs 8-bit word-based permutations, as opposed to the standard GFN's 16-bit word-based cyclic shifts. The key schedule is based on permutation for greater hardware efficiency. PICCOLO takes fewer rounds, consumes less power, and has a greater throughput than other GFNs. PICCOLO is, however, susceptible to biclique cryptanalysis [50]. SLIM [51] is a symmetric 32-bit block cipher based on the Feistel structure. Controlling SLIM is an 80-bit key. Like with other symmetric block ciphers, encryption and decryption use the same key. SLIM contains four 44 S-boxes that execute a non-linear operation on a 16-bit word and serve as a non-linear component of the cipher. The creators of SLIM assert that it is immune to differential cryptanalysis because they were only able to find a trail of up to seven rounds using a heuristic method. On this cipher, no other cryptanalysis attacks have been attempted. Nonetheless, SLIM's key size is deemed insufficient to provide appropriate security in actual contexts [52]. IoT lightweight cipher designs are required to have robust encryption standards, robust architecture, low complexity, rapid execution time, minimal power consumption, low resource utilization, and great resilience to potential assaults. Despite this, a considerable number of attacks against ciphers that are thought to be resistant have been uncovered. As a result, the construction of lightweight block ciphers has attracted the attention of various academics, particularly in the last five years. An exhaustive literature assessment on lightweight block ciphers demonstrates that the currently available ciphers are not fully optimized, allowing room for future research. Therefore, the hunt for a lightweight cipher that fits the requirements of a good cipher continues.