esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
In this work, the disc cutter wear and breakage morphologies were observed. The cutting edge rounding (CER) and flank wear \(VB\) were introduced to characterize the wear characteristics, and the diameter reduction and the cutting edge breakage width were used to characterize the breakage characteristics of the disc cutter. Additionally, the characterization parameters were used to analyze the disc cutter wear process in the ultrasonic cutting Nomex honeycomb core. The conclusions can be summarized as follows:  
Figure 23: Ultrasonic cutting machining surface with disc cutter under different cutting lengths. (a) 0 m; (b) 23.25 m; (c) 46.50 m; (d) 69.75 m; (e) 93.00 m.  
Figure 22: Conventional cutting machining surface with disc cutter under different cutting lengths. (a) 0 m; (b) 23.25 m; (c) 46.50 m; (d) 69.75 m; (e) 93.00 m.  
The tool wear forms of the disc cutter are mainly cutting edge wear and flank wear. The wear positions are concentrated near the cutting edge, which is shown as the cutting edge dulling and the flank wear band. The CER and the flank wear \(VB\) increase with the increase in the cutting length. The CER increases from 3.54 \(\upmu\)m to 8.26 \(\upmu\)m, and the increasing trend is more significant. The disc cutter wear mechanism is mainly abrasive wear.
2. The tool breakage form of the disc cutter is mainly the cutting edge breakage. The breakage positions are primarily at the cutting edge, which manifests as chipping and cracking breakage. With the increase of cutting length, the width of cutting edge breakage gradually increases; the continuous chipping makes the breakage form of the disc cutter show a band distribution; and the overall diameter of the disc cutter gradually decreases.
3. The length and quantity of burrs on the honeycomb surface increase gradually with the increase in the degree of disc cutter wear and breakage. Ultrasonic cutting results in fewer honeycomb burrs and better surface quality compared to conventional cutting at the same cutting condition.  
Conceptualization, L.L. and Y.W.; methodology, L.L. and Y.W.; software, Y.Q.; validation, R.K., Z.D. and H.S.; formal analysis, Y.Q. and Y.W.; investigation, L.L.; resources, Z.D., data curation, L.L.; writing--original draft preparation, L.L.; writing--review and editing, Y.W.; visualization, Z.D.; supervision, H.S.; project administration, R.K.; funding acquisition, R.K. All authors have read and agreed to the published version of the manuscript.  
This study was supported by the National Natural Science Foundation of China (Grant No. U20A20291) and Dalian High-Level Talent Innovation Program (Grant No. 2020 RD02).  
Not applicable.  
All the authors are greatly acknowledged for their financial support in making this research possible.  
The authors declare no conflict of interest.
# Digitalizing Industrialized Construction Projects: Status Quo and Future Development
## 4 Qualitative Analysis
### Operation and Maintenance Phase  
#### 4.4.1 Predictive Maintenance  
Predictive maintenance is a fundamental strategy in building operation that leverages data to predict potential problems in building facilities. Through systematic monitoring and data analysis, this approach facilitates proactive maintenance or repair interventions, preempting equipment failures or performance declines. Predictive maintenance is widely used in industrialized construction, where it aims to reduce downtime, improve equipment reliability, and ultimately reduce operating costs.  
Predictive maintenance begins with meticulous data collection and monitoring. Utilizing modern mapping tools or sensors proves instrumental in this endeavor. [PERSON] et al. [91]integrated sensor data with BIM to effectively visualize structural health assessment components. Similarly, [PERSON] [92] showcased how modern mapping tools, such as unmanned aerial systems, digitally captured physical building data and features to evaluate building damage for emergency management purposes. Given the diversity in building types and materials, tailored data collection and monitoring programs are imperative. For instance, [PERSON] et al. [93] adopted varied monitoring techniques for reinforced concrete beam half-joints, encompassing traditional inspection systems alongside emerging structural health monitoring techniques. Moreover, [PERSON] et al. [94] underscored the versatility of digital technologies in structural health monitoring, utilizing laser scanning and digital image analysis to continuously monitor the health of precast concrete bridges under diverse hydraulic conditions.  
The digital twin model emerges as a pivotal tool for predictive maintenance, furnishing enhanced predictive capabilities while mitigating modeling uncertainties. The model significantly improves the predictive accuracy of vulnerability curves. For example, [PERSON] et al. [95] introduced the PRESSAFE-disp (PRecast Existing Structure Seismic Assessment by Fast Evaluation displacements) methodology, which involves collecting a wide range of data related to prefabricated buildings to create a comprehensive database. By categorizing these data, the methodology expedites seismic loss assessment and retrofitting decisions for large-scale prefabricated buildings. For prefabricated concrete bridges, [PERSON] et al. [96] developed a digital twin model integrating structural health monitoring with computational finite element modeling, enabling the formulation of seismic fragility curves to underpin post-disaster decision-making strategies. These advancements underscore the significance of predictive maintenance in refining operation practices, where the proactive identification of potential issues hold paramount importance. However, existing studies primarily focus on individual project types, necessitating more generalized methodologies.
## 5 Result and Discussion
### Effect of Batch Size  
Most of the training of deep learning models is based on mini-batch stochastic gradient descent (SGD). At this time, the batch size is one of the important hyper-parameters when training the actual model. Various studies are being conducted regarding the effect of the batch size on model training. Although it has not been clearly identified yet, it is experimentally observed in several studies that the use of a small batch size has a positive effect on generalization performance. We experimented with the effect of learning rate [16, 32, 64, 128, and 256] on performance.  
Figure 5 shows the effect of batch size for ConvNet, DocClass_ConvNet_Mod, and RepSTDoc_ConvNet. In the representative spatio-temporal learning data used in this study, there was no consistent performance variability across models. RepSTDoc_ConvNet shows a tendency to improve performance as the batch size increases in the model training section [32, 64, 128, and 256]. However, in DocClass_ConvNet_Mod, the variation of performance according to the batch size was not consistent. Although this result cannot be generalized, the batch size may not affect the performance of the model depending on the complexity of the CNN layer and the characteristics of the data.
# 3D Liver and Tumor Segmentation with CNNs Based on Region and Distance Metrics
## 3 Experiment and Discussion  
### Experimental Preparation and Protocols  
We conducted an evaluation of two datasets for liver and tumor segmentation, and the examples of the data are shown in Figure 3.  
LiTS 2017: Liver Tumor Segmentation Challenge (LiTS) dataset [34] provides 201 contrast-enhanced 3D abdominal CT scans, and segmentation labels for liver and tumor regions with a resolution of \(512\times 512\) in each axial slice. There are 131 scans providing ground-truth labels, and 70 scans that do not provide labels. The in-plane resolution ranges from 0.60 mm to 0.98 mm, and the slice spacing from 0.45 mm to 5.0 mm. We clipped the intensity values to the range [\(-\)300, 400] HU to ignored irrelevant details and normalized the images into [0, 1].  
3D-IRCADb: 3D Image Reconstruction for Comparison of Algorithm Database (3D-IRCADb) is a database containing anonymous medical images of several groups of patients, as well as manual segmentation of various structures of interest by clinical experts. The database consists of 3D CT scans of 10 women and 10 men with liver tumors. The in-plane resolution ranges from 0.57 mm to 0.87 mm, and the slice spacing from 1.6 mm to 4.0 mm. All scans were performed while the arterial phase was in the inhaled position.  
We trained the four 3D V-Net models with regional loss and other three distance-based loss functions in two databases. The experiments were conducted with Torch and optimized with the Adam algorithm [35] on four NVIDIA Tesla V100 GPUs. (Gigabyte Technology, Beijing, China) When the deep models were trained, a batch size of 2 and a learning rate of 0.001 were employed. Of them, the learning rate was divided by five after 200 epochs, and the training ended after 1400 epochs. For fairly comparing the diverse loss functions, the models were tested on the test set after every 40 epochs, and the best models were utilized for the contrast test.  
Figure 3: The scans in Liver Tumor Segmentation Challenge (LiTS) 2017 dataset and 3D Image Reconstruction for Comparison of Algorithm Database (3D-IRCADb).  
As mentioned above, the value of \(\alpha\) in Equations (1)-(3) was set to 1 from the initial training to 400 epochs. Afterward, it was reduced by 0.01 every 10 epochs till reaching 0.01. Therefore, only the regional loss was used for training at the beginning, and then the distance-based loss influence gradually increased. According to our results, the as-proposed convenient scheduling strategy always gave superior results over the constant value.
## 3 Methodology  
### Problem Statement  
Accurate prediction of port container throughput is a key link for optimizing intermodal cooperative operation. In order to break through the limitations of traditional forecasting methods, this paper proposes a data-driven forecasting framework to improve the accuracy of throughput prediction by constructing a multidimensional time series regression model, so as to optimize the operational efficiency of ports and promote the efficient collaboration between logistics chains and suppliers. To this end, we design a multidimensional indicator screening framework and innovatively propose a WACNN prediction model. The model takes the screened and data-enhanced multi-source time series indicator data as input, and makes a regression prediction of target data through multiple indicators. The input matrix is shown below:  
\[(X_{1},X_{2},\ \ \ldots\,X_{m})=\left[\begin{array}{cccc}x_{11}&x_{12}& \ldots&x_{1m}\\ x_{21}&x_{22}&\ldots&x_{2m}\\ \ldots&\ldots&\ldots&\ldots\\ x_{n1}&x_{n2}&\ldots&x_{nm}\\ \end{array}\right] \tag{1}\]  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Literature** & **Data Filtering** & **Data Enhancement** & **Prediction Model** & **The Best Model** \\ \hline [PERSON] [7] & ✓ & ✓ & SM & ARIMAX \\ [PERSON] [22] & \(\times\) & ✓ & ML & LSTM \\ [PERSON] [24] & \(\times\) & \(\times\) & ML & RF \\ [PERSON] [25] & ✓ & \(\times\) & DL & BP \\ [PERSON] [36] & \(\times\) & ✓ & DL & LSTM \\ [PERSON] [37] & \(\times\) & \(\times\) & DL & LSTM \\ [PERSON] [39] & \(\times\) & ✓ & DL & LSTM and GRU \\ [PERSON] [40] & \(\times\) & ✓ & DL & BiLSTM \\ This study & ✓ & ✓ & DL & WACNN \\ \hline \hline \end{tabular}  
* BP: backpropagation neural network; SM: statistic model; RF: random forest; GRU: gated recurrent unit.  
\end{table}
Table 1: Summary of literature containing predictive models.  
where \(X_{1}\),\(X_{2}\),...,\(X_{m}\) represent \(m\) sets of indicator data, and \(x_{11},x_{12},\ \ldots\,x_{mm}\) represent \(m\) sets of indicators, each with a total of \(n\) days of data.
## 2 Overview of Navigation Systems  
The last two decades have seen an increasing trend in the use of global navigation satellite systems (GNSS) in a variety of positioning and navigation applications. The GNSS receiver determines the satellite's antenna position, and lever arm compensation is utilized to deduce the receiver position for GPS/RISS integration. GNSS applications include but are not limited to passenger cars, taxis, buses, ambulances, police cars, farming vehicles, fire trucks, and mobile robots [10]. Current navigational systems match the position on the digital map with the help of information from GNSS. Improved digital maps assist in the enhancement of navigational systems [10; 11]. Intelligent transport systems (ITS) focus on bringing features like collision warning and mitigation, lane-keeping, lane-changing with route guidance to the desired destination, traffic flow guidance, vulnerable road user detection, driver condition monitoring, and improved vision. These features need navigation systems with higher accuracy and better reliability, availability, and continuity of service [12]. Moreover, GNSS has played a major role in the navigation of unmanned aerial vehicles (UAV), utilizing single or multiple satellite constellations [13]. The researchers utilized a space-based augmentation system (SBAS) to produce an improved positioning for the UAV by 19-22% compared to the single constellation. Furthermore, GNSS, INS, and light direction and ranging (LiDAR) systems have been combined to improve the orientation of low altitude UAVs utilized in coastal applications [14]. The proposed system reduced the orientation error from 0.5 degrees to 0.01 degrees. Although the solution  
Figure 1: Illustration of the input/output block diagram of a system.  
provided by GNSS is sufficiently accurate (especially when used in differential mode), it is not able to accomplish the requirements of continuity, reliability, and availability. GNSS may suffer from outages, interference, jamming, spoofing, and multipath effects in urban canyons and rural foliage canopies, as shown in Figure 2[15]. Thus, GNSS alone cannot fulfill the requirements of service for modern navigation systems. In [16], a sidelobe cancellation technique introduced to the multipath effect could be used in GNSS receivers.
# Design of an Eye-in-Hand Smart Gripper for Visual and Mechanical Adaptation in Grasping
###### Abstract  
With the advancement of robotic technologies, more and more tasks in industrial and commercial applications rely on the use of robots to assist or even replace humans. To fulfill the needs of grasping and handling different objects, the development of a universal grasping device acting as an end-effector to a robotic manipulator has been one of the main robotic research and development focuses. Therefore, this study was aimed at the development of a general robotic gripper with three fingers for adaptive actuation and an eye-in-hand vision system. With the adaptive actuation feature, each finger of the robotic gripper contained multiple degrees of freedom that allowed the finger to change its shape to wrap around an object's geometry adaptively for stable grasping. With the eye-in-hand configuration in the adaptive gripper, it offered advantages including occlusion avoidance, intuitive teleoperation, imaging from different angles, and simple calibration. This study proposed and integrated a plug-and-play gripper module, controller module, and visual calculation module all in the model smart gripper, of which the gripper was further validated by calibrated experiments. The proposed gripper featured mechanical adaptation and visual servoing adaptivity to achieve 100% gripping success rate when gripping a moving target of any shape that was carried by conveyor belt with moving speed less than 70 mm/s. By integrating mechanical and visual adaptivity, the proposed gripper enabled the inclusion of intelligence in robotic applications and can further be used in smart manufacturing and intelligent robotic applications.  
adaptive gripper; compliant; eye-in-hand; under-actuated; vision tracking Article
## 1 Introduction
In the reordered palette, two colors with adjacent color indices may not be similar; some selected pixels may have large embedding distortion, which degrades image quality after data embedding. Furthermore, the color indices of some selected pixels may overflow or underflow after data embedding. To avoid using these blocks, an additional location map is required to record if a block is used to embed secret data. This reduces the embedding capacity for secret data because some blocks are skipped and some are used to embed the location map. To address the aforementioned problem, a novel BBM for palette images was proposed in this study. First, [PERSON] et al. 's \(k\)-bit parity assignment [14] was used to assign a \(k\)-bit parity to each color in the palette of an image. Then, for each block, at most one pixel was modified for data embedding, and no location map was required for data extraction. The proposed method provided higher capacity. Note that the primary goal of steganographic methods [21] is to develop statically undetectable methods with high steganographic capacity. Steganographic capacity [21] is defined as the maximum number of bits that can be hidden in a given cover work, such that the probability of detection by an adversary is negligible. The embedding efficiency [21] is one kind of measure for undetectability, and it is defined as the number of embedded random message bits per embedding change. [PERSON] [22] mentioned that the most obvious method to reduce the possibility of detecting hidden information is to reduce the change density in the cover image. Since decreasing the change density raises the embedding efficiency, higher embedding efficiency will lower the detectability. Since BBMs reduce the change density, the detectability of these methods is lower. To measure the undetectability of the proposed method, chi-square attack [23], RS steganalysis [24], and embedding efficiency are used. Estimation and experimental results demonstrated that the proposed method provided higher undetectability than the aforementioned BBMs [16; 17]. The remainder of this paper is organized as follows. Related works are introduced in Section 2. The proposed method is presented in Section 3. The analysis of embedding capacities is given in Section 4. Experimental results are provided in Section 5. Finally, conclusions are presented in Section 6.
## 4 Potential IIoT Applications  
A wide variety of challenging applications is foreseen for IIoT [74, 75]. These applications can be categorized into two groups: the delay-tolerant ones related to mMTC and forecasting/monitoring applications and the delay-sensitive ones regarding enhanced SCADA, time-critical IIoT, and URLLC. The former ensures E2E massive connectivity and energy efficiency, but at the expense of augmented delay. More specifically, delay-tolerant applications tend to be those encompassing large land and remote or sea areas, e.g., energy and smart grid, oil and gas pipeline integrity, and tracking of mining trucks. Applications regarding disaster and crisis management in industrial environments are also worth mentioning. Despite the link with factories, manufacturing, and heavy industries, the term IIoT is also used to describe several IoT applications outside of the consumer IoT in the context of facility management, such as agriculture, transport systems, and healthcare. Figure 4 summarizes indicative types of sensors and potential applications with respect to the NTN-based IIoT.
# Target Localization Based on Bistatic T/R Pair Selection in GNSS-Based Multistatic Radar System
## 4 Simulation and Experimental Results  
An experiment is conducted to evaluate the performance of Covariance Matrix Fusion Method (CMF method) and Convex Hull Optimization Method (CHO method). They are verified through maritime target positioning experiment using the GNSS-based passive multistatic radar.
# Code Obfuscation: A Comprehensive Approach to Detection, Classification, and Ethical Challenges
## 4 Between Best Practices (ITIL Framework) and Obfuscation Techniques
### Practical Considerations for CIOs When Implementing Code Obfuscation  
The implementation of code obfuscation presents both challenges and opportunities for Chief Information Officers (CIOs). On the challenge side, obfuscated code can be significantly harder to maintain and debug, resulting in increased time and resource demands for troubleshooting and updates due to its convoluted nature. Performance overheads are also a concern, as obfuscation may slow down applications; for example, gaming applications might experience longer loading times and noticeable lags, which can negatively impact user experience. Additionally, code obfuscation can conflict with regulatory requirements for transparency and auditability, potentially requiring the creation of a separate, deobfuscated version of the code to meet audit demands. However, code obfuscation also offers significant opportunities. It enhances application security by making it more difficult for attackers to understand and exploit the code, thereby protecting customer transactions and maintaining system integrity. Furthermore, it safeguards intellectual property by preventing competitors from easily replicating unique solutions, helping the company maintain a competitive edge. Additionally, a strong commitment to security through code obfuscation can enhance customer trust and confidence, leading to increased user adoption and higher customer retention. To effectively leverage code obfuscation, CIOs must strategically address key factors such as identifying critical areas for protection, ensuring tool compatibility and effectiveness, equipping internal teams with the necessary skills, monitoring performance impacts, and complying with local regulations. By carefully balancing these considerations, CIOs can harness the benefits of code obfuscation while managing its complexities.
## 6 The Use of CBCT in Orthodontics in the Pediatric Population
The results indicated a 12.15% reduction in central incisor root volume on the cleft side compared to the side without cleft. In addition, it was found that the development of the central incisor root was significantly more dependent on the cleft (which had a smaller volume) in the female gender. The data obtained may help in planning orthodontic treatment for patients with UCLP. Another paper by [PERSON] et al. [87] compared the effectiveness in evaluating \"dens invaginatus (DI)\" (a developmental anomaly where enamel invaginates into dentin) using CBCT and panoramic images rendered from CBCT images. As a result, it was found that analysis of panoramic images detected DI in 3% and CBCT images in 10.7% of patients. These results demonstrate the greater usefulness of CBCT in diagnosing DI compared to panoramic images, due to its accurate representation of the external and internal anatomy of the tooth. In the last cited study by [PERSON] et al. [88], 20 CBCT images were taken in pediatric patients with unilateral posterior crossbite without functional mandibular displacement and with transverse jaw loss. The mandibular condyles on the right and left sides and between the crossed and uncrossed sides in sagittal and frontal views were then measured. The precise images obtained with CBCT indicated that there were no significant differences in the described dimensions, in contrast to indications in the literature suggesting an association between the size of the mandibular condyles and the presence of unilateral posterior crossbite in children.