esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Structural Design
### Hopping Mechanism Design
#### 2.1.1 Design Objectives  
To meet the requirements of continuous hopping with fast response, simple and reliable energy storage/release, the first research objectives of this paper is established as:  
(1) Using only one motor that is as small as possible.  
(2) The motor should only rotate unidirectionally.  
Due to the inherent characteristic in kinematics of the hopping mechanism, it will add unnecessary angular momentum to the robot system if there is a horizontal component of ground reaction force (GRF) in the direction of take-off, thereby endangering the stability of hopping posture. For example, the direction of the GRF should be close to the vertical direction when the robot's take-off angle is 90\({}^{\circ}\). Based on this requirement, the second research objective of this paper is proposed as: achieving non-rotation or minimal rotation of the robot (sagittal plane) to take-off, which means the robot take-off with near-zero angular velocity and the system has no additional angular momentum. To materialize this requirement, we present the following two design objectives:  
(3) The foot trajectory curve of the hopping mechanism should (a) be a straight line; (b) pass through the center of mass (CM) of the robot; (c) be consistent with the take-off direction of the hopping robot.  
(4) Minimize the moment acting on the robot's CM when the robot component moves.  
At the same time, for the miniaturization of the robot, the following design objectives are proposed:  
(5) The foot trajectory curve of the hopping mechanism should be located within its mechanism.  
(6) The structure of the hopping mechanism is compact.
# In Situ Study of Surface Morphology Formation Mechanism During Laser Powder Bed Fusion
## 3 Results and Discussion
### Evolution of Melt Pool Characteristics
#### 3.1.2 Melt Pool Temperature Distribution  
Our research investigates the temperature distribution characteristics of the melt pool and the impact of process parameters on the thermal behavior of the melt pool based on infrared monitoring data. Figures 4 and 5, respectively, display the temperature distribution of the melt pool under different laser power and scanning speed conditions. From the temperature field distribution of the melt pool, it can be concluded that the temperature gradient decreased gradually from the center to the edge of the melt pool as heat was transferred. The temperature gradient at the front of the melt pool was greater than that at the tail end. This is because during the advancement of the melt pool, the thermal conductivity of the metal powder at the front was lower than that of the molten liquid at the tail end, allowing heat transfer to occur more rapidly at the tail end of the melt pool than at the front [8]. The temperature of the melt pool increased with the increase in laser power, and the area of the melt pool also increased under greater energy input. Additionally, under high laser power, the temperature values along the centerline of the melt track are higher, and the temperature curve is steeper, indicating that changes in laser power affected the temperature gradient levels of the melt pool. The effect of scanning speed showed an opposite trend. As the scanning speed increased, the time during which the laser interacted with the powder bed became shorter, resulting in a decrease in both the melt pool area and temperature. Comparing the rate of temperature change in the melt pool between Figures 4 and 5, it can be found that, compared to scanning speed, laser power had a more significant impact on the temperature gradient of the melt pool, which is consistent with the conclusions in [8; 26].  
Figure 4: The effect of laser power on the temperature distribution of the melt pool: (**a**) \(P=200\) W (Supplementary Video ESM_5); (**b**) \(P=250\) W (Supplementary Video ESM_6); (**c**) \(P=300\) W (Supplementary Video ESM_7); (**d**) \(P=350\) W (Supplementary Video ESM_8); (**e**) \(P=400\) W (Supplementary Video ESM_9); (**f**) the effect of laser power on the temperature distribution along the centerline of the melt track (\(V=80\) mm/s).
# Low-Power Wireless Data Transfer System for Stimulation in an Intracritical Visual Prosthesis
## 2 System Considerations  
### System Requirements  
The overall system for the visual prosthesis will have many requirements for the system components various levels. We will now list the requirements related to the wireless communication system.  
1. Low-power communication: based on power consumption reported in [18; 19], the projected power consumption of the implant side of the 1000 electrodes visual prosthesis without wireless interface is on the order of 100 mW. This estimate includes neural recording electronics and the stimulation drivers. Considering the wireless power transfer, and battery constraints at the implant side, it is desired that the wireless system add to more than 10-30% extra power to the power budget at the implant side.
2. Data rate: if the stimulation pulses are to be transmitted in raw form, the total number of commands for a stimulation is 4 for a biphasic signal: (1) turn on the cathodal current; (2) turn it off; (3) turn on the anodal current; (4) turn it off. Each electrode needs to be refreshed at a rate of about 200 Hz for physiological reasons [20]. With this approach, the required data rate reaches a few Mbps. The implanted neurostimulation driver will take care of the waveform for stimulation. Only wireless communication to the driver is considered here. Therefore, from a video rate perspective coupled with a de-multiplexing scheme on the implant side, such as reported in [20], the minimum required communication data rate is 200 kbps (20 frames per seconds, 1000 electrodes per frame, and 10 bits per electrode). We aim for the 200 kbps.
3. Robustness to interference from power carrier: in the visual prosthesis, the implanted side will be powered wirelessly to reduce battery size constraints. The wireless power that reaches the implant side is of the order of 20 dBm [21], and the received data power can be in the order of \(-\)60 dBm. Thus, the power signal can be about 80 dB larger than the data signal. This power ratio may prove to be a challenge,especially when power transfer and communication take place simultaneously and at frequencies close together. Care must be taken that the frequencies are properly spaced to ensure that practical filters can be used without consuming a considerable amount of power.
4. Bit error rate: neural scientists desire that in the worst case, only one percent of the phosphene pixels is an error. If each electrode is encoded by 10 bits, then the worst case bit error rate target is \(10^{-3}\). A much better bit error rate is preferred for robustness, the exact value is still unknown.
5. Security: with the rise of worldwide security breaches, measures must be taken to avoid hacking and re-writing of the brain. One of such measures could be taken at the physical layer by employing close range communication, which is inherently safer.
## 4 Experiments and Results
### Experiment 3: Industrial Images Test  
In this experiment, the five methods are applied to process six industrial images with some defects as shown in Figure 2g-l.  
The six defect images results achieved by different methods are shown in Figure 11a-f. There is no reference image that can be applied to calculate PSNR or SSIM, so the standard variance (STD) and entropy will be applied to evaluate the results.  
It is difficult to locate the defect in the original version of industrial image 1 directly by vision. After the five methods applied on indust1, the defect becomes clearer than the original, and it can be found that the proposed result is better than others (as shown in Figure 11a). The inhomogeneous background is removed from the main part of our result, while it can still be found in other results.  
The suspect defect in the second image is very weak in vision, and it is also difficult to be found. The traditional methods strengthen the background difference between top part and bottom part. In this situation, it is disadvantageous to find a weak defect deeply hidden in a part of the background for the over-smoothing on each part. Our method excludes the inhomogeneous background, and the weak defect is more significant than other results (as shown in Figure 11b).  
Though the main defects in the last four images are easy to be found and all the methods treat it well, some small features (maybe defects in other scenes) are smoothed in the results of PM, TV and CTAD. It seems that the [PERSON]'s model better protects the features than our model because it preserves abundant details (suspect area). In fact, most of them are unnecessary details or noise; it may result in a more expensive check cost.  
STD and entropy of the results are listed in Table 7. It can be found that the proposed method achieves the minimal STD or entropy on each image, that is, the results show less confusion and more regularity in the view of information theory.  
Figure 10: Iteration numbers.  
Figure 11: Results of Industrial images in Experiment 3.
## 3 Methodology
### Data Acquisition and Text Embedding
#### 3.1.1 Data Acquisition  
We initiated our research by collecting 6G patent data in five emerging fields, namely, NSTs, RISs, ISAC, ISAGSC, and EAIs. All the related patent records were retrieved and collected from the Incopat database [52], a globally renowned patent information platform with abundant patent resources. In order to ensure a comprehensive collection of relevant  
Figure 1: Our dynamic topic modeling framework for exploring the emerging technologies in 6G over time.  
patents in these fields, this study retrieved the data using specific search formulas set by experts and obtained 78,625 patent records in 6G after an initial screening process for eliminating irrelevant patents. Figure 2 shows these technological fields in 6G have been highly active in recent years and contain many emerging technologies in these five fields, which may potentially attract more industry attention. The patents' titles and abstracts, being the primary repositories of condensed yet valuable technological information, were extracted for further pre-processing.  
Consequently, the abstracts and titles were pre-processed to reduce noise for subsequent analysis. Inspired by the work of [PERSON] [53], we employed an LLM-based summarization process to eliminate noise in the technical context and enhance the performance of dynamic topic modeling for 6G patent text analysis. In the context of dynamic topic modeling in analyzing technological trends in 6G, the patent data are often voluminous and contain a wealth of information, including technical details, background knowledge, and future research directions. Neural-based topic models like BERTopic show promise in topic modeling but can be further optimized with more concise and directed input. Secondly, the large amount of noise and domain-specific jargon in 6G patent texts can obscure the underlying themes. Summarization can help distill the essential information, reduce noise, and improve the quality of topic modeling.
## 3 Memristive Analog Design
### Oscillators
This improvement in performance makes it suitable for various applications, such as communication systems, signal processing, and data encryption. The discussed works investigate the use of memristors to design RF oscillator circuits for wireless communication applications. The studies focus on the advantages of using memristors in oscillator design, such as improved frequency tunability and reduced circuit complexity compared to traditional designs. The presented results are schematic simulations, demonstrating the feasibility and potential performance enhancements of memristor-based RF oscillators. Further experimental validation is needed to confirm the practicality of implementing these designs in real-world wireless communication systems. Several issues need to be addressed. One issue with using memristors to implement oscillators is their susceptibility to noise, which can affect the stability and performance of the oscillator. Another concern is the limited frequency range that memristors can operate at, which may restrict the potential applications of the oscillator in certain scenarios. Additionally, the non-linear behavior of memristors could introduce unwanted harmonics into the oscillator output, affecting signal quality. Furthermore, the variability in memristor characteristics can also lead to inconsistencies in frequency output, making it challenging to achieve precise and reliable oscillation. In order to mitigate these issues, careful design and characterization of memristors are necessary for successful implementation in RF oscillator circuits. Also, methods like adaptive tuning and feedback control can be used to fix the nonlinearities and variations in memristors, which makes the oscillator work better overall. Overall, addressing these challenges will be crucial for realizing the full potential of memristor-based RF oscillators in future electronic systems.
# Bilateral Teleoperation System with Integrated Position/Force Impedance Control for Assembly Tasks
## 4 Control Algorithms
### Master-Remote Position Controller  
As a traditional algorithm, a simple position control method was carried out in the remote assembly robot. The remote manipulator tracked the trajectory of the operator based on the captured motion information, and the remote gripper opened or closed according to the signal of bending sensors on the fingers. When the object was grasped, the grasping force was mapped to the operator's perception with haptic feedback gloves. Since the wearable wireless tracker has a wide workspace, we were able to set a position scaling factor \"K\" between the movement of the operator and the motion of the remote robot to achieve a more precise remote assembly. For comparison with the method below, in this study, we set \"K\" to 1.
###### Abstract
The considered EAHFSP is more general and complex than AHFSPs, EHFSPs, and other energy-related shop scheduling problems. This means that EAHFSP is also NP-hard. Therefore, it is essential to develop an effective and efficient algorithm to investigate EAHFSPs, in which energy costs and total production costs are regarded equally important. The artificial bee colony (ABC) algorithm is an excellent metaheuristic algorithm that simulates the foraging behavior of bee colonies in nature [32]. Its extraordinary features, such as effective global search ability and fast convergence capability, have been proven in many complicated optimization problems [33; 34; 35; 36]. Moreover, the ABC algorithm also has many successful applications in various scheduling problems. [PERSON] et al. [37] applied a multi-objective ABC to a flexible job shop scheduling with maintenance. [PERSON] et al. [38] proposed a hybrid ABC algorithm for blocking lot-streaming flow shop scheduling. [PERSON] et al. [39] developed an improved ABC algorithm for hybrid flow shop scheduling. [PERSON] et al. [40] presented a novel ABC algorithm for parallel batching distributed flow-shop scheduling. [PERSON] et al. [41] proposed an ABC algorithm with division to investigate distributed parallel machine scheduling. The ABC algorithm is also utilized to solve assembly shop scheduling [42] and energy-efficient shop scheduling [43]. However, the ABC algorithm is rarely used to investigate EAHFSPs. The excellent characteristics of the ABC in scheduling problems encourage us to study EAHFSPs by improving the ABC algorithm. In this study, an AHPSP considering energy consumption is investigated, which widely exists in production but without enough attention. Moreover, this is the first time that a green scheduling objective and an adjustable processing speed set are added to an AHPSP. The main features are as follows. (1) A multi-objective EAHFSP is investigated, and a mathematical model is built. (2) A novel DABC is proposed to minimize the makespan and total energy consumption simultaneously. In the employed bee phase, diversified search strategies are constructed, and the suitable search strategy is adaptively selected based on the rank value of food sources. In the onlooker bee phase, a novel probability selection method is introduced to select the tracking objects, and the number of neighborhood searches is different for each food source; a diversity enhancement strategy is utilized to maintain the diversity of food sources and avoid prematurity. (3) Extensive comparative experiments are executed to demonstrate the effectiveness of DABC in solving the EAHFSP. The novelties of this paper are summarized in Table 1.  
The remainder of this paper is organized as follows. A description of the problem is provided in Section 2. A description of the ABC algorithm is given in Section 3. A DABC method for EAHFSPs is proposed in Section 4. Computational experiments using the DABC algorithm are provided in Section 5. The conclusions and prospects are reported in Section 6.
## 7 Simulation and Evaluation
### Performance Metrics
#### 7.1.3 Routing Overhead  
Routing Overhead measures the extra communication required for maintaining the routing information, indicating the efficiency of the protocol.  
MMS-DSR exhibits lower routing overhead compared to SOL-DSR, Enhanced OLSR, and traditional DSR, as depicted in Figures 13 and 14. The overhead increases from 200 control packets at 10 vehicles/km\({}^{2}\) to 1600 control packets at 100 vehicles/km\({}^{2}\) and from 200 control packets at 10 km/h to 1550 control packets at 100 km/h. This is significantly lower than the 2000 control packets required by Enhanced OLSR and DSR. MMS-DSR's on-demand routing strategy, combined with the predictive capabilities of LSTM networks, minimizes unnecessary control packet transmissions, thus reducing overhead and improving overall network efficiency.  
A key advantage of MMS-DSR is its ability to predict vehicle movements without relying on GPS systems. By utilizing predictive models that anticipate vehicle trajectories,  
Figure 11: Route discovery time vs. vehicle density.  
Figure 12: Route discovery time vs. vehicle speed.  
MMS-DSR reduces the need for frequent route updates, which significantly lowers the routing overhead. This approach ensures efficient use of network resources and enhances the protocol's scalability and adaptability in urban VANET environments.  
As vehicle density and speed grow up, MMS-DSR maintains lower overhead by efficiently managing control packet transmissions and preventing unnecessary route discoveries. For example, at a vehicle density of 50 vehicles/km\({}^{2}\), MMS-DSR requires only 1000 control packets compared to 1500 for Enhanced OLSR.
### Goals and Contributions  
The purpose of this article is to introduce our work in developing a unique and efficient method of classifying _cybersecurity feature claims_ (henceforth simply referred to as \"claims\"). The final architecture resulting from the research presented in this paper that is aimed at determining a model achieving maximum classification accuracy is based on a pre-trained BERT language model combined with a Convolution Neural Network (CNN) to create a feature map for extracting informative features from transformers and then assigning them to a classifier. Specifically, for our work we define a claim as any sequence that expresses a claim in regards to the availability, or lack of availability, of a cybersecurity feature in a given product. Sequences that make unrelated claims or that are not making any such claims, are subsequently labeled as not containing a cybersecurity claim. As part of this research we studies the impact of various different NN feature map approaches, different activation functions, and more.  
Figure 1: Overall workflow of the CYVET cybersecurity vetting framework.  
The resulting ClaimsBERT is a classification model enabling our framework to automatically identify any cybersecurity claims present in ICS device documents. The contributions of this work are summarized in the following items:  
1. We introduce a new concept of ClaimsBERT to significantly enhance base model BertForSequenceClassification, by integrating CNN feature maps in order to improve performance and accuracy;
2. We present our findings obtained using extensive experiments for optimizing our model's overall architecture and its hyperparameters;
3. We discuss the effectiveness of a suitable feature map in parameter selection in our proposed architecture for ClaimsBERT;
4. We show that our model achieves a high classification accuracy of 97 percent;
5. We discuss the results of our extensive evaluation of ClaimsBERT and its performance comparison with other network-based BERT models. The results indicate that significantly higher accuracy is obtained when integrating CNN into original BERT classifier and fine-tune all layers.
## 3 Results and Discussion
### Analysis of Damage Evolution
While the strain level is less than 0.010, a negligibly small amount of bonds are broken and no detailed analysis of cracks is required. However, as the uniaxial compression load increases, multiple new microcracks initiate, propagate, and eventually coalesce into longer macroracks. The initiation, accumulation, and propagation of shearing microcracks can be observed in the left upper region \"I\", as presented in Figure 4a-d. At the end of the time interval of slow microcrack propagation, seven microcracks are already detected in this region (Figure 4b). Five microcracks are detected on the right upper surface region numbered by \"II\" at the end of the time interval of medium microcrack propagation, shown in Figure 4b. However, in the time interval of fast macro crack propagation, the number of observed microcracks reaches ten and twelve, as presented in Figure 4c,d, respectively. Figure 4c,d shows that, during the time interval of fast macro crack propagation, the smallest increase of microcrack number is observed in the bottom right surface region \"III\". Different crack propagation in different regions is caused by asymmetrical distribution of material pores, directly implemented in the discrete element packing by using the micro-CT scan. Figure 4c,d shows that the main macroscopic shearing cracks form during the time interval of microcrack transfer to macroracks, and propagate during the time interval of fast macro crack propagation in the surface regions \"I\" and \"IV\" of the sample. Some macroscopic cracks suddenly propagate, leading to final failure of the sample. It is worth noting the fragmentation of the sample into more than two parts, which is common to failure patterns observed in uniaxial compression experiments of brittle materials.
## 2 Materials and Methods
### Characterization of Infrared Absorption Spectrum  
The defect structures of Zn:Cu:Fe:LiNbO\({}_{3}\) crystals were systematically characterized using Fourier-transform infrared (FTIR) spectroscopy. Infrared absorption spectra were acquired using an AVATAR370 spectrometer(Thermo Fisher Scientific, USA) under consistent experimental conditions, with a spectral range of 3400-3600 cm\({}^{-1}\), corresponding to the characteristic OH\({}^{-}\) stretching vibration region. This analytical approach is particularly effective for defect structure analysis, as identical molecular groups and bond types exhibit characteristic and reproducible absorption peaks [28].  
During crystal growth, the H\({}^{+}\) ions from both the raw materials and growth atmosphere incorporate into the LiNbO\({}_{3}\) lattice, predominantly existing as OH\({}^{-}\) groups [29]. The OH\({}^{-}\) stretching vibration demonstrates exceptional sensitivity to local ionic environments, making infrared spectroscopy an invaluable tool for investigating ion occupancy and defect configurations in LiNbO\({}_{3}\) crystals. The precise analysis of OH\({}^{-}\) absorption bands provides critical insights into the distribution and coordination of dopant ions within the crystal lattice.