esa-sceva/satcom-chunk-collection huggingface dataset:
# A Secure and Lightweight Group Mobility Authentication Scheme for 6 LoWPAN Networks
## 6 Performance Evaluation
### Discussion
#### 6.5.2 Signaling Cost  
According to the comparison of signaling costs, SL_GAS generates a lower signaling overhead than the other schemes, mainly when a handover occurs within a handover. Table 4 shows that SL_GAS reduces message signals to \(n+6\), the lowest value among the schemes, resulting in lower network congestion. In environments where many devices are operated, minimizing the signaling overhead is crucial to avoid bottlenecks in the communication infrastructure. However, SL_GAS is designed to balance security and efficiency by optimizing cryptographic operations using LiCi-128, reducing authentication overhead with ticket-based mechanisms, and minimizing transmission overhead through aggregated MACs and optimized message exchanges. Compared to [16] (\(4n+10\)), SL_GAS reduces signaling overhead by 40%, making it more suitable for large deployments. While [20] (\(2n+2\)) grows rapidly with increasing \(n\), SL_GAS remains manageable even in high-density environments. Thus, SL_GAS keeps inter-gateway communication efficient as the network  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Parameters** & **Energy Consumption (\(M\)j)** \\ \hline SL\_GAS for a group of 10 nodes & 8.987 \\ \hline SL\_GAS for a group of 50 nodes & 36.876 \\ \hline SGMS for a group of 10 nodes & 9.621 \\ \hline SGMS for a group of 50 nodes & 39.682 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Energy cost comparison for authentication during handover.  
expands, preventing excessive overhead that may compromise the performance of the network. This efficiency improves the network's overall performance, especially under heavy load.
# PPDC: A Privacy-Preserving Distinct Counting Scheme for Mobile Sensing
###### Abstract  
Mobile sensing mines group information through sensing and aggregating users' data. Among major mobile sensing applications, the distinct counting problem aiming to find the number of distinct elements in a data stream with repeated elements, is extremely important for avoiding waste of resources. Besides, the privacy protection of users is also a critical issue for aggregation security. However, it is a challenge to meet these two requirements simultaneously since normal privacy-preserving methods would have negative influence on the accuracy and efficiency of distinct counting. In this paper, we propose a Privacy-Preserving Distinct Counting scheme (PPDC) for mobile sensing. Through integrating the basic idea of homomorphic encryption into Flajolet-Martin (FM) sketch, PPDC allows an aggregator to conduct distinct counting over large-scale datasets without disrupting privacy of users. Moreover, PPDC supports various forms of sensing data, including camera images, location data, etc. PPDC expands each bit of the hashing values of users' original data, FM sketch is thus enhanced for encryption to protect users' privacy. We prove the security of PPDC under known-plaintext model. The theoretic and experimental results show that PPDC achieves high counting accuracy and practical efficiency with scalability over large-scale data sets.  
Keywords:distinct counting; privacy-preserving; mobile sensing; flajolet-martin sketch; secure bitwise XOR +
Footnote †: journal: Applied Sciences
# Design and Stability Analysis of Six-Degree-of-Freedom Hydro-Pneumatic Spring Wheel-Leg
## 2 Dual In-Wheel Motor Wheel-Leg
### Functional Characteristics  
(1) Bearing longitudinal loads: During braking and acceleration, longitudinal loads are resisted by the corresponding hydro-pneumatic springs and tension springs. The impacts are dissipated through damping holes, as shown in Figure 2(a). The blue line represents the extended state of the hydro-pneumatic spring, and the red line represents the compressed state of the hydro-pneumatic spring. The red wavy line represents the extended state of the tension spring, and the black/blue wavy line represents the compressed state of the tension spring.  
(2) Bearing lateral loads: During turning and side-slipping, lateral loads are resisted by the corresponding hydro-pneumatic springs and tension springs. The impacts are dissipated through damping holes, as shown in Figure 2(b).  
(3) Bearing vertical loads: In the case of uneven road surfaces, vertical loads are quickly responded to by the hydro-pneumatic springs and tension springs, as shown in Figure 2(c).  
(4) Horizontal steering: During differential steering of the wheelset, the torque generated by the hydro-pneumatic springs is counteracted by the correction force of the tension springs, providing resistance to disturbance torques, as shown in Figure 2(d).  
According to the qualitative analysis above, the six-arm hydro-pneumatic spring suspension, aided by tension springs, can withstand loads from various directions. While  
Figure 3: Force analysis of the wheel-leg system under different load directions.  
Figure 2: Dual in-wheel motor wheel-leg system.  
tension springs offer the advantage of reducing the unsprung mass and improving the suspension response under vertical loads, the instability issues during steering require further quantitative study.
## 3 System and Model Description
### Attacking Model
This attacking process on an ACD node is called a single-step attack, taken as an atomic process. Secondly, to improve the successful attacking probability, single-step attacks can be launched repeatedly until a successful attack or a service migration occurs. Due to the replacement of suspicious SCVs after the voting process, the experience gained from performing repetitive attacks on the same node cannot be accumulated indicating that in this context, the attacks are memoryless, and they can be modeled that way. Finally, depending on the offensive and defensive results obtained over each migration period, the attacker moves along the attack chain and changes its target. The movements among different migration periods correspond to the upper layers of Figure 1, and we focus on analyzing the movements of the attacking locations in the third part of the analysis. The timeline of attacking is shown as Figure 3.  
Figure 2: The Attacking Process. Therefore, the attacking processes in the blockchain cloud can be analyzed from the three layers as shown in Figure 4, including single-step attacks, repetitive attacks against one node over a migration period, and attacker movements among different migration periods. According to the characteristics of the defensive process in each layer, we propose a three-layer model named SPM to analyze the effectiveness of an ACD network. SPM is a hybrid model combining multiple theoretical methods, including Stochastic Petri nets, Poisson process, Markov chain, and Martingale theory. Similar to most theoretical models [64], we do not aim at evaluating the system parameters into an absolute security value but in relative terms to the set under evaluation. Several assumptions are adopted from [7; 19; 23] to simplify the analysis:  
1. The attacker compromises one blockchain node at most in each migration period. 2. Node information is wholly changed after migration, so the attacking difficulty will be the same when attacking the same node again. 3. The probability of compromising each node is independent and identically distributed. 4. In the third part of the SPM model, only the node under attack and the node from which attacks originated are considered in the migration process, which results in attack failure, and the attacker is repelled. 5. All time intervals are assumed to be exponentially distributed.
# IoT Blockchain Data Vercity with Data Loss Tolerance
## 5 Conclusions  
While many IoT systems are struggling with inevitable data loss, various technologies have been studied with regard to mitigating this data loss problem. One of the potentials is coupling IoT with blockchain technology, and it is gaining wide acceptance in data loss avoidance.  
This paper presented a workable IoT blockchain with strength monitoring model in enhancing the data veracity. The experimental results show that the proposed IoT blockchain can alleviate data loss, contributed by the peer-to-peer network (P2P) and distributed ledger storage technology (DLT). Both the small computing resources evaluation and LT-SPICE simulation meet the expected results, no data loss occurred in the event of single or multiple node failure, and the data was still maintained by the survived redundant nodes. The proposed IoT blockchain is further enhanced with strength monitoring, through its capacitance, and the LTSPICE simulation results proved that the strength can be measured by its capacitance. Capacitance increases in proportional to the number of nodes; any capacitance deterioration will trigger an alert to prevent any system crash.  
The proposed framework is proven to be an applicable model for IoT deployment in a scarce infrastructure resources environment such as plantations and other industries that may often experience data loss problems. The proposed framework and simulation models can serve as a reference for further enhancement in IoT and blockchain-based data veracity studies.  
**Author Contributions:** Formal analysis, K.C.M.; investigation, K.C.M.; writing--original draft preparation, K.C.M.; writing--review and editing, T.J.L.; supervision, T.J.L.; review, D.K.; and All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was conducted in Universiti Teknologi PETRONAS (UTP) under the Fundamental Research Grant Scheme (FRGS) funded by the Malaysia Ministry of Higher Education (MOHE) with the reference code of FRGS/1/2019/ICT01/UTP/02/1, the project ID of 17508, the selected grant of FRGS 2019-1, and the project title of \"Generic Consensus Model for Improving Nodes Syndicating Performance in Blockchain\".  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# QoS-Aware Scheduling Algorithm Enabling Video Services in LTE Networks
## 3 LTE Schedulers  
Providing satisfying QoS to active users is considered a key challenge for resource allocation with regards to every transmit time interval (TTI), since available resources need to be distributed on the network amongst users in order to cater to their requirements. LTE employs scheduling techniques in order to effectively use resources with regards to time and frequency bands [20]. For both uplink and downlink, packet scheduling mechanisms have been applied at eNBs for the MAC layer, in which allocation of the physical resources is done for downlink and uplink channels. Parts of the shared spectrum are assigned by the eNB to each user by complying with specific policies. The distribution of Resource Blocks (RBs) is controlled by the packet scheduler to cater to the needs of Users' Equipment (UE) and evade cell interference. In general, scheduling aims to achieve appropriate allocation pertaining to the basic physical resource block (e.g., frequency, time, power, etc.) to cater to users' equipment, which quenches the demand for QoS by users through specific scheduling patterns such as traffic type, channel condition, queue status, and head-of-line packet delay, which is based on the prioritised packet scheduler decided by the users; it also determines which UE needs to be scheduled and assigned with regards to the PRBs [21]. Figure 1 illustrates the general model for downlink packet scheduling over LTE networks.  
Nonetheless, various issues exist with regards to the design of an LTE system solution and numerous downlink packet scheduling algorithms have been created to cater to QoS and fairness needs for different LTE optimisation services.  
Thus, a brief explanation has been provided of the four different scheduling algorithms compared against the proposed method put forward in a simulation scenario, pertaining to MLWDF, PF, EXPRule, and EXP/PF.
## 3 Experimental Studies and Results  
We consecutively applied the model to three major communicative situations, in which (a) the robot tells a human a story, so the denotatum is represented by the robot; (b) the human has to solve a special puzzle and the robot follows the solution and gives advice--here the denotatum is explicitly represented to both the human and the robot; (c) the robot listens to a story that is being told by the human, and therefore, the denotatum here is represented by the human. In all these conditions, the robot has to apply different gaze control modes to balance between the social (responsive) gaze, the side gaze, and the gaze to the physical object in problem space, if it exists. Although natural gaze behavior is rather compound and may differ in varying communicative situations, we iteratively extended the suggested model in order to cover these conceptually symmetric types of communicative situations.  
In general, eye movements tend to have at least an implicit influence on the robot's attractiveness to a user. In our recent study [35], we investigated the contribution of the robot's effectors' movements--such as those of the hands, head, eyes, and mouth--to their attractiveness to the user. The subjects were students, teachers, and counselors of an educational camp (\(n=29\), 17 females, mean age of 19). During the experiment, the subjects were asked to listen to five short stories narrated by the robot. The subjects had to listen to each story twice in random order--with the robot using all active organs--_full-motion mode_, and without movements of a specific active organ (no movement of the eyes, head, hands, and no mouth animation)--deficit mode. After presenting two experimental conditions for each story, the subject chose their most preferred type of the robot's behavior. The subjects were also asked to describe the difference between the two modes of storytelling by the robot. As expected, the subjects in all cases chose the robot that used full-motion behavior. The experimental study revealed that users are more likely (\(p<0.01\), Mann-Whitney U-test) to prefer a robot that uses gestures, head movements, eyes, and mouth animation in its behavior compared to a robot for which some part of its body is stationary. The impact of the robot's eye movements on the user was quite implicit; the subjects significantly more often (\(p<0.05\), Mann-Whitney U-test) preferred the robot with eye movements to the robot with motionless eyes, but they seldom (\(p<0.05\), Mann-Whitney U-test) explicitly noticed the difference between these two modes. The implicit nature of the preference was supported by the verbal responses to a subsequent questionnaire; the subjects rather indicated the irrelevant differences between the robots, for example, they assumed that one of the robots spoke faster, said something wrong, or was in some way kinder and/or more interested.
# Experimental and Numerical Investigation of the Mesoscale Size Effect in Notched Woven Composites
## 1 Introduction
The central concept is the use of an FEM simulation that provides a faithful representation of the stress fields in the tested specimen while remaining computationally manageable. A 2D shell model is built, taking into account the information on the local changes of material direction obtained from the DIC data and image processing. The properties are determined with data-driven optimization, minimizing the difference between the DIC-measured and FEM strain fields. Thereafter, the calibrated model is used to analyze the stress concentration and localization induced by circular notches with increasing diameter, revealing two counteracting effects related to the size effect. Even though the volume subjected to stress intensification increases with the notch diameter, an increase in the carbon fiber tow strength following that in the stress localization has been observed, partially compensating for the stress intensification induced by the notch. The structure of this article is as follows. Section 2 contains a detailed description of the material tested, the mechanical tests performed, the construction of the numerical model with the aid of image processing, the finite element analysis, the data-driven parameter identification, and the methods used to study the size effect. The results of the experimental tests, numerical modeling, and parameter and size effect studies are reported in Section 3. Finally, Section 4 contains a discussion of the strengths and weaknesses of the model construction process and the model itself, and concludes with the findings on the size effect in circular notches.
## 3 Materials and Methods
### Analysis of Volatile Compounds  
Volatiles were analyzed using HS-SPME method. Crushed, dried, and fresh leaf samples of approximately 0.25 g were added in glass vials with 2 \(\mu\)g of _p_-methoxyphenyl as an internal standard. Glass vials were covered with a polytetrafluoroethylene (PTFE)/silicone septum and subsequently placed in a water bath at 60 \({}^{\circ}\)C for equilibration for 10 min. Extraction was performed using SPME fiber (Supelco, Bellefonte, PA, USA) with a vivinylbenzene/carboxen/polydimethylsiloxane fiber (divinylbenzene/Carboxen/polydimethylsiloxane (DVB/CAR/PDMS), 50/30 \(\mu\)m, coating 2 cm) (Supelco). The SPME fiber was conditioned by inserting it into a gas chromatography injection port at 220 \({}^{\circ}\)C for 1 h before extraction was conducted. Then, the SPME fiber was inserted into the vial containing the sample that was kept in a water bath at 60 \({}^{\circ}\)C for 30 min. The fiber was withdrawn into the needle and injected into the injection port of GC-MS at an injection temperature of 220 \({}^{\circ}\)C for 3 min. GC-MS analysis was conducted on a Varian CP-3800/Saturn 2000 (Varian, Wallnut Creek, CA,USA) equipped with a ZB-5 MS capillary column (30 m \(\times\) 0.25 mm inner diameter (i.d.) \(\times\) 0.25 \(\upmu\)m film thickness).  
The initial oven temperature was kept at 50 \({}^{\circ}\)C, raised to 130 \({}^{\circ}\)C at a rate of 4 \({}^{\circ}\)C min\({}^{-1}\), subsequently increased to 180 \({}^{\circ}\)C at 10 \({}^{\circ}\)C min\({}^{-1}\), and finally increased to 280 \({}^{\circ}\)C at a rate of 2 \({}^{\circ}\)C min\({}^{-1}\). Helium was used as a carrier gas at a flow rate of 1.0 mL min\({}^{-1}\). The samples were manually injected in a split mode (split mode 1:10). Mass spectra were obtained in an electronic ionization (EI) mode of 70 eV with a scan range of _m/z_ 35-550. After each extraction was completed, the SPME fiber was placed in the injection port of GC-MS at 220 \({}^{\circ}\)C for 15 min to ensure that volatiles were completely eluted to prepare for the subsequent extraction. Volatiles were identified by comparing the mass spectra of the compounds obtained experimentally, and the mass spectra were available in the NIST14 database. The retention index (RI) experimentally determined by [PERSON] was compared with the RI in NIST WebBook and literature data [43]. Quantification of identified compounds was calculated by comparing the peak area of individual compounds with the peak area of the standard used, _p_-methoxyphenol, with a concentration of 1 mg/mL.
# Data Gathering Techniques in WSN: A Cross-Layer View
## 5 Routing for Data Gathering in WSN
### Data Collection Utilizing Mobile Sink and Unmanned Aerial Vehicle (UAV)
#### 5.4.2 Cluster-Based Data Forwarding
The data transmitted by CH to UAV is pre-processed by a specialized optimized compression. A genetic algorithm for energy-efficient CH selection is employed by [PERSON] et al. [188]. The focus of [PERSON] et al. [189] is on MS that traverses a WSN that relies on a cluster-based data collection protocol in which cluster-heads are responsible for collecting and transmitting the cluster members' sensed data to the MS. The paper examines a scenario in which the MS is constantly moving in a predefined trajectory, regardless of whether the data transfer was completed or not. Accordingly, when the cluster aggregate data is toolarge, the CH cannot complete the transaction. The authors suggest a mechanism in which, in case the CH cannot complete the transaction, it can use different cluster members as relays to continue the transaction after the MS has moved out of the transmission range of the CH. Likewise, [PERSON] et al. [190] also suggest a hybrid approach that combines the MS with hierarchical routing-based protocol relying on node clusterization. In order to improve the efficiency of the MS data collection, [PERSON]. [190] suggests utilizing virtual heads (VHs) that lie on the MS trajectory on the cluster boundaries that also transmit collected data to the MS. The channel access relies on a random access mechanism. The UAV can be of different physical structures. While some machines are able to slow down and even to hover, others, especially the winged UAVs, can only fly with a constant velocity. This limitation poses an additional challenge; see [PERSON] et al. [191] for a possible solution. To address the velocity limitation, the grid topology of the UAV's coverage is divided into frames, and the most distant frames get the highest priority. The priority-based transmissions from sensors to the moving UAV are incorporated into a MAC layer, by introducing a priority-based contention window adjustment scheme. A smaller contention window is assigned to the frame where sensors send packets from the rear side of the UAV, and should therefore have a higher transmission priority. This results in a low packet loss when the UAV flies forward. On top of this architecture, a frame-selection-based routing protocol is formulated.
# Wavelet-Enhanced YOLO for Intelligent Detection of Welding Defects in X-Ray Films
###### Abstract  
Welding defects threaten structural integrity, demanding efficient and accurate detection methods. Traditional radiographic testing defects interpretation is subjective, necessitating automated solutions to improve accuracy and efficiency. This study integrates wavelet transform convolutions (WTConv) into YOLOv11n, creating WT-YOLO, to enhance defect detection in X-ray films. Wavelet transforms enable multi-resolution analysis, extracting both high-frequency and low-frequency features critical for detecting various welding defects. WT-YOLO replaces standard convolutional layers with WTConv, improving multi-scale feature extraction and noise suppression. Trained on 7000 radiographic images, WT-YOLO achieved a 0.0212 increase in mAP75 and a 0.0479 improvement in precision compared to YOLOv11n. On a test set of 200 images per defect category across seven defect types, WT-YOLO showed precision improvements of 0.0515 for cracks, 0.0784 for lack of fusion, 0.0067 for incomplete penetration, 0.1180 for concavity, 0.0516 for undercut, and 0.0204 for porosity, while experiencing a slight 0.0028 decline for slag inclusion. Compared to manual inspection, WT-YOLO achieved higher precision for cracks (0.0037), undercut (0.1747), slag inclusion (0.1129), and porosity (0.1074), with an inference speed 300 times faster than manual inspection. WT-YOLO enhances weld defect detection capabilities, providing the possibility for a robust solution for industrial applications.  
a Article  
[PERSON], [PERSON], [PERSON], [PERSON], Q. Wavelet-Enhanced YOLO for Intelligent Detection of Welding Defects in X-Ray Films. _Appl. Sci._**2025**, _15_, 4586. [[https://doi.org/10.3390/appr15084586](https://doi.org/10.3390/appr15084586)]([https://doi.org/10.3390/appr15084586](https://doi.org/10.3390/appr15084586))
## 2 Background
### Driving Technologies of Industry 4.0
#### 2.2.11 Radio Frequency Identification (RFID)  
Involves the sharing and transfer of data to identify and track tags of various types of objects and assets through automatic identification [7; 58; 75]. Each industrial device has an identification and tracking tag with a unique number [7]. The use of RFID in industries enables greater visibility, coordination, and control of the supply chain [75].