esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Investigation of the Influence of Major Parameters on the Pipeline Damping Performance
### Effect of Particle Materials on the Pipeline Damping Performance
#### 4.2.1 Comparison of Three Particle Materials at a 20% Filling Rate  
Figure 8 and Table 1 show the responses in the time domain and RMS values of the damped pipeline. When the cavity was filled with steel particles, the RMS of the response decreases by 35.7% compared with that of the bare pipe. Meanwhile, when filling with steel balls, the damping effect was improved by 10.4% and 25.3% compared to filling with aluminum and glass balls, respectively.  
Figure 9 shows a comparison of the vibrational response of different particle materials with the bare pipe. Compared with the bare pipe, the particle impact damper filled with 20% steel balls, aluminum balls, and glass balls showed a shift in the first-order resonance frequency, and the resonant amplitude was significantly reduced. Among them, the resonant frequency shifts of the damped pipeline filled with steel balls were about 60 Hz, and the corresponding resonant amplitude was reduced by 68.8%. When the damped pipeline system was filled with aluminum and glass balls, the resonant amplitudes were reduced by about 55.9% and 26.3%, respectively. It is concluded that the vibration reduction effect of the particle impact damper filled with steel balls is the best due to the low value of the restitution coefficient and the relatively high mass effect.  
\begin{table}
\begin{tabular}{c c c} \hline
**Pilot Protocol** & **RMS/g** & **Vibration Reduction Effect \(\Delta\)** \\ \hline Bare pipe & 78.7 & — \\ Steel ball & 50.6 & 35.7\% \\ Aluminum ball & 56.5 & 28.2\% \\ Glass ball & 67.7 & 14.0\% \\ \hline \end{tabular}
\end{table}
Table 1: Three materials with 20% filling rate under random excitation.  
Figure 8: Time responses of damped pipeline with different materials at a 20% filling rate.  
Figure 7: Three kinds of particle materials. (**a**) Steel ball; (**b**) Aluminum ball; (**c**) Glass ball.
## 7 Conclusions  
At the cost of low data rates, LPWAN technologies supply long-range, low-power, and low-cost communication. In this paper, we discussed the common features LPWAN technologies employ, and their characteristics were tested in terms of various aspects, including bandwidth, modulation, data rate, range, link budget, maximum payload, power efficiency, security, adaptive data rate, localization, allowing private networks, battery lifetime, and availability. In addition, we showed how to pick the technology suitable for the field of application. On the other hand, LoRa technology as an emerging trend for IoT applications was the main focus among the LPWAN technologies in this paper. Among LPWAN technologies, LoRaWAN offers several advantages, including an open standard, low power consumption, long-range transmission, built-in security, the possibility of private deployments, and GPS-free geolocation. In addition, duty cycle constraints and low data rate LoRaWAN networks are the advantages of real-time application in Class B. Therefore, the investigations of LoRaWAN issues obtained by deploying LoRaWAN networks are discussed carefully. Furthermore, we evaluated recent approach solutionsand presented some possible methods. However, some still have open issues such as network management, optimization ADR, high-density LoRaWAN installations, and device interoperability that need to be addressed more for practical use.  
Conceptualization, M.A.M.A.; methodology, M.A.M.A. and W.A.J.; analysis and writing--original draft preparation, M.A.M.A. and W.A.J.; writing--review, W.A.J. and N.S.; project administration, W.A.J.; funding acquisition, W.A.J.; editing M.A.M.A., W.A.J. and S.A. All authors have read and agreed to the published version of the manuscript.  
This research work was funded by Universiti Malaysia Pahang (UMP) under the research grant PDU203229 and the post-graduate research scheme PQRS200340.  
The authors disclose that they have no conflicting interests.
## 3 A KMS Design Challenge with AMI System  
The standard components of any KMS may include key management frameworks, key generation and refreshment rules, key distribution policies, and key storage techniques. Conclusions about the challenges of creating the KMS may be drawn from the AMI's structure and messaging as follows:  
* Hybrid transmission techniques are utilized in bidirectional communications, such as broadcast, unicast, and multicast. It is expected that the KMS will be able to accommodate all of these transmission modalities. In order to find a solution to this issue, the KMS must be adaptable enough to accommodate all three distinct forms of transmission. The protocols governing the production, updating, and distribution of keys are each crafted specifically for each mode.
* The NXs are usually implemented using embedded systems. When compared to a typical computer or server, they are less powerful both computationally and in terms of storage. Additionally, the messages call for limited-time broadcasts. The key generation and refreshing algorithms are most significantly impacted by NXs' low computational capabilities. Primarily, quite simple cryptographic methods like hashing might be utilized. Additionally, the frequency of key distribution should be kept to a minimum because of the restricted time for message delivery. Similarly, it is best to reduce the number of keys and other relevant data that must be saved in NXs.
* Projects using DR users do not have fixed users. Depending on their preferences and needs, they may choose projects at various periods. Users who participate in the same DR project may band together to establish groups; these users are known as group members.
* Due to the dynamic nature of group participation in DR projects, ensuring both forward and backward security in the multicast mode becomes critical. New users should be assigned to groups when they join the project, and each group member should receive new keys and additional data to ensure secure communication. While users who leave the project no longer receive updates, shared keys, and additional data should be refreshed frequently to preserve security.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Message Type** & **Sender** & **Receiver** & **Transmission Mode** & **Time Requirements** \\ \hline \multirow{2}{*}{Meter data} & NX & DMS & Unicast & \textless{}15 s \\  & DMS & NXs & Broadcast & \textless{}15 s \\ \hline \multirow{2}{*}{Joining or leaving the DR} & NX & DMS & Unicast & \textless{}15 s \\ \hline \multirow{2}{*}{Pricing} & DMS & NXs/DR & Broadcast/multicast & \textless{}15 s \\ \hline \multirow{2}{*}{Remote control} & DMS & NXs/DR & Broadcast/multicast & \textless{}5 s \\ \hline \multirow{2}{*}{Notifications} & NX & DMS & Unicast & \textless{}5 s \\ \hline \multirow{2}{*}{Publishing DR} & DMS & NXs & Broadcast & \textless{}5 s \\ \hline \hline \end{tabular}
\end{table}
Table 1: AMI messages with transmission mode and time requirements [19].
###### Abstract  
The purpose of this paper is to report the results of a laboratory experiment that investigated how assortment planners' perceptions, usage behavior, and decision quality are influenced by the way recommendations of an artificial intelligence (AI)-based recommendation agent (RA) are presented. A within-subject laboratory experiment was conducted with twenty subjects. Participants perceptions and usage behavior toward an RA while making decisions were assessed using validated measurement scales and eye-tracking technology. The results of this study show the importance of a transparent RA demanding less cognitive effort to understand and access the explanations of a transparent RA on assortment planners' perceptions (i.e., source credibility, sense of control, decision quality, and satisfaction), usage behavior, and decision quality. Results from this study suggest that designing RAs with more transparency for the users bring perceptual and attitudinal benefits that influence both the adoption and continuous use of those systems by employees. This study contributes to filling the literature gap on RAs in organizational contexts, thus advancing knowledge in the human-computer interaction literature. The findings of this study provide guidelines for RA developers and user experience (UX) designers on how to best create and present an AI-based RA to employees.  
recommendation agent; artificial intelligence; decision-making; transparency; cognitive effort; perception; behavior; decision quality; eye tracking Article Recommendation Agent Adoption: How Recommendation Presentation Influences Employees' Perceptions, Behaviors, and Decision Quality  
[PERSON], [PERSON], [PERSON], [PERSON], and [PERSON]. (2019) 20  
In this paper, we answer the following research question: How does the way recommendations of an AI-based RA are presented influence assortment planners' perceptions (i.e., source credibility, sense of control, decision quality, and satisfaction), usage behaviors, and decision quality? Based on the literature on the consumer context, we expect that the perceptions, usage behavior, and decision quality of consumers and assortment planners will align even though their RA adoption process differs. This study contributes to filling the gap in the literature on RAs in organizational contexts and provides insights for RA developers and user experience (UX) designers on how to best present an AI-based RA to employees for them to consider and adopt its recommendations.
###### Abstract  
The occurrence of musculoskeletal diseases (MSDs) among oil palm harvesters has been studied extensively, but there is a lack of published studies on the evaluation of the range of harvesting movements. This information is important to design the ergonomic tools needed in the manual harvesting of oil palm. We examined the upper limb motion of oil palm harvesters to determine the effects of age and initial shoulder postures on their range of harvesting movements. Twenty male harvesters performed a manual push-pull-cutting technique (\(\geq\)3 m fresh fruit branches (FFBs) height). The study was conducted by capturing the 1-D push-pull cutting technique harvesting movement via the Quintic system at the sagittal plane. The active range of harvesting movements during the harvesting phases and the range of the harvesting movement of the initial and maximum postures of their upper arms were calculated based on the kinematic data generated with the Quintic Biomechanics system (Version 29). Participants were divided into three groups based on their age, and two groups based on their initial support shoulder position, and dominant shoulder position. Data were analysed using the ANOVA and \(t\)-test. The joint movement angle pattern of the harvesters was classified into three phases: preparation, execution, and ending. The age-related variances for the initial and maximum support shoulder postures were determined. The range of harvesting movements and the active range of harvesting movements during the preparation phase at the support shoulder and wrist region were also observed. The initial support shoulder posture displayed a statistical variance in the maximum support and dominant range of harvesting movements of the shoulder. It was also linked to a reduced active range of harvesting movements for the support shoulder flexion and dominant wrist ulnar deviation at the preparation phase. Furthermore, the initial dominant shoulder exhibited a statistically significant difference for the dominant arm and a reduced active range of harvesting movements in the dominant wrist ulnar deviation at the preparation phase. This study produced important evidence about factors to be considered for the ergonomic design of harvesting tools and workplaces, especially within the oil palm industry.  
musculoskeletal disorders (MSDs); oil palm harvesters; active range of harvesting movements; upper arm; Quintic Biomechanics system +
Footnote †: journal: Applied Sciences
## 4 Experiments and Result Analysis
### Evaluation Metrics  
The confusion matrix is required to calculate the evaluation index. The confusion matrix is a table that stores the actual classification results in the dataset as well as the  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Feature** & **Description** \\ \hline PA1:VH-PA3:VH & Phase A-C Voltage Phase Angle \\ PM1:V-PM3:V & Phase A-C Voltage Phase Magnitude \\ PA4:IH-PA6:IH & Phase A-C Current Phase Angle \\ PM4:I-PM6:I & Phase A-C Current Phase Magnitude \\ PA7:VH-PA9:VH & Pos.-Neg.—Zero Voltage Phase Angle \\ PM7:V-PM9:V & Pos.-Neg.—Zero Voltage Phase Magnitude \\ PA10:VH-PA12:VH & Pos.-Neg.—Zero Current Phase Angle \\ PM10:V-PM12:V & Pos.-Neg.—Zero Current Phase Magnitude \\ F & Frequency for relays \\ DF & Appearance Impedance for relays \\ PA:Z & Appearance Impedance for relays \\ PA:ZH & Appearance Impedance Angle for relays \\ S & Status Flag for relays \\ control\_panel\_log & control panel remote trip status \\ relay\_log & relay status for relay1–4 \\ snort\_log & snort alert status for relay1–4 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Dataset features and descriptions.  
Figure 5: Experiment network diagram.  
prediction results of the classification model in machine learning as a matrix. Table 2 depicts the confusion matrix proposed in this paper.  
In Table 2, TA represents the model's correct detection of attack records, while FA represents the model's misinterpretation of normal system operations as an attack on the system. TN, on the other hand, is a normal record of the model's correct judgment, whereas FN is a misjudgment that the system is under attack during normal system operations. The confusion matrix can be used to assess the proposed model's performance. The goal of this experiment is to reduce the number of RF classifier's FN and FA. We assess our intrusion detection model against this goal using four commonly used effectiveness metrics: precision, recall, accuracy, and F1-score.  
The above indicators' calculation formulas can be expressed as:  
\[\text{Accuracy}=\frac{\text{TA}+\text{TN}}{\text{TA}+\text{TN}+\text{FA}+ \text{FN}} \tag{4}\]  
\[\text{Precision}=\frac{\text{TA}}{\text{TA}+\text{FA}} \tag{5}\]  
\[\text{Recall}=\frac{\text{TA}}{\text{TA}+\text{FN}} \tag{6}\]  
\[\text{F1}=2\times\frac{\text{precision}\times\text{recall}}{\text{precision}+ \text{recall}}=\frac{2\text{TA}}{2\text{TA}+\text{FA}+\text{FN}} \tag{7}\]
###### Abstract  
This paper describes a prototype of a free-space transmission setup for dielectric parameters estimation. The transmitter and receiver, both configurable by software and working in the range 0.85-1.55 GHz, are not synchronized, as they use different clocks. An estimation of the dielectric permittivity of a planar sample was obtained by comparing our measurements with a numerical model. A parametric study with different variables was conceived in order to find the best fit between measurements and simulations. Customized techniques were applied to deal with noise and inconsistencies found in the measurements. The genetic algorithm was used to adjust the constants that minimized the error between simulated and experimental data. Results for a reference sample of polymethylmethacrylate are presented and discussed. Although the accuracy of the proposed approach in recovering the dielectric parameters of the sample was relatively low, the simplicity and cost-effectiveness of this setup make it interesting for scenarios where a rough characterization of the material is sufficient.  
free-space method; materials characterization; software-defined radio Article  
Estimation with Affordable and Non-Synchronized Software-Defined Radios in the 0.85-1.55 GHz Band
# Investigation of Visual Stimulus Signals Using Hue Change for SSVEP
In general, a flash stimulus is used for the visual stimulus presented in the generation of SSVEP [3]. Flash stimuli include red light-emitting diodes and periodically inverted black-and-white images displayed on the display. In recent years, exploiting the advantage that flash stimuli can be readily prepared, liquid crystal displays (LCDs) have been used to show black-and-white flash stimuli, and research on game manipulation by BCI has been conducted [5]. In contrast to the advantage that flash stimuli can be readily prepared, there is a problem in that the brightness of the flash stimulus signal used is intense and causes eye irritation. Thus, it causes fatigue and discomfort, is difficult to use for extended periods, and has a risk of inducing photosensitive epilepsy [4]. Therefore, methods causing less irritation and less discomfort are actively being studied. For example, an attempt has been made to reduce fatigue and discomfort by changing the luminance value of the flash stimulus as a sinusoidal or triangular wave and decreasing the abrupt change in brightness [6]. In this article, we focus on the fact that asthenopia and mental fatigue during visual display terminal work are related to display colors reported in [7] and propose a visual stimulation method that does not cause eye fatigue or discomfort by generating visual stimulation signals using three primary colors of light in the flash stimulus. The proposed method produces a flash stimulus by changing the hue of the color of the stimulus, which was previously changed by changing the brightness. The aim of this paper is to experimentally clarify the visual stimulus signals that cause the least discomfort to users by using the proposed visual stimulus signals of each of the three primary colors and asking users a subjective questionnaire about their discomfort for each color.
# A Novel Drone Design Based on a Reconfigurable Unmanned Aerial Vehicle for Wildfire Management
## 6 PULSAR Applications in Forest and Wildfire Management
### Payload Categorization and Integration
#### 6.4.1 LiDAR Sensor [Phoenix RECON XT]  
The LiDAR RECON-XT (Phoenix LiDAR, Austin, TX, USA) laser mapping system represents an exceptional fusion of performance, flexibility, and weight optimization in the field of LiDAR technology. Designed primarily for UAVs, the RECON-XT stands out as the leader within its weight class. Notably, it offers a distinctive advantage with its exceptional versatility in mounting options.  
Moreover, the RECON-XT showcases its impressive capabilities through its multi-target capacity, significantly expanding its operational scope. This advanced LiDAR sensor enables the collection of highly detailed and accurate 3D point cloud data, making it the preferred choice for professionals seeking efficient and flexible solutions for mapping and surveying projects [46].  
The technical specifications of the selected sensor (Table 2) are presented next, followed by the custom payload case that will be developed and the configuration that will be housing it (Figure 15).  
\begin{table}
\begin{tabular}{l c} \hline \hline
**Parameter** & **Value** \\ \hline \multirow{2}{*}{Overall dimensions (L \(\times\) W \(\times\) H)} & Platform \\  & 207 \(\times\) 112 \(\times\) 157 mm \\  & 1.8 kg \\   Camera resolution & 24 MP \\   Power consumption & 20 W Typical \\  & LiDAR sensor \\   Laser properties & 905 nm Class 1 (eye safe) \\   Range max & 120 m \\   RMS ranging error & 10 mm (Average within 0.5–70 m @50\% \\   Pulse rate & 640 k points/s, up to 1.28 M points/s dual \\   Field of view & +15–16\({}^{\circ}\) vertical/360\({}^{\circ}\) horizontal \\   Multiple echoes & 2 \\   Number of lasers & 32 \\   Beam divergence & 2.29 mrad/1.52 mrad \\  & 90 mm \(\times\) 60 mm @40 m \\   Laser beam footprint H \(\times\) V & 140 mm \(\times\) 90 mm @60 m \\  & 180 mm \(\times\) 120 mm @80 m \\ \hline \hline \end{tabular}
\end{table}
Table 2: Phoenix RECON XT—Technical Specifications.
## 3 APD Breadboard Design and Implementation
### Sensor Test Chamber  
To avoid water vapor condensation at negative temperatures, the APD was tested in a vacuum environment. To achieve this, a test vacuum chamber was designed and manufactured in our laboratories. It consisted of a main body made from stainless steel with a Viton O-ring sealant on one of the extremities, an aluminum main heat sink (MHS), a broadband precision window (N-BK7 WG11508-C coated) (WG), and a sensor holder plate (SHP). Three high performance TECs were positioned between the MHS and SHP.  
The temperature was monitored with two 10 k\(\Omega\) negative temperature coefficient thermistors, one positioned near the sensor and the other on the MHS. The electric interfaces (air-vacuum) were a DEE-Glenair (DG) connector to supply the circuits and the thermistors and a high-power electric interface to power the three TECs current-voltage connector (CIV).  
Outside the vacuum chamber, attached to the MHS, were two copper braids connected to an optical table to help dissipate the heat. There was a fourth TEC between the MHS and a smaller second heat sink attached to the optical table, cooled by a small 12 V fan.  
The chamber walls were covered by multi-layer insulation (MLI) (6 by-layers) to further provide thermal insulation for the sensor. Coupled with the chamber window, there was a ML925B45F Mitsubishi laser diode (LD), operating at 1550 nm, to inject a radiant flux into the chamber. The test setup chamber CAD design and its components can be seen in Figure 8.  
Initial tests performed with a vacuum enclosure showed that the system could sustain vacuum environments as low as 7.4 Pa and stable temperature values on the holder plate from 324 K down to 243 K, thus achieving the necessary conditions to test the sensors. The image of the chamber fully manufactured is provided in Figure 9.
# Reversible Data Hiding in Encrypted Image Based on Multi-MSB Embedding Strategy
## 3 Details of Selection of Parameters
### Parameters of Maximum Embedding Rate  
In this paper, the data is embedded into the multi-MSB of pixels, and the embedding capacity of an image is _Cap_ which has been introduced in Section 2.3. In fact, the embedded data include secret bits and bit planes of edged pixels. Thus, the pure embedding capacity of secret bits is actually (_Cap_-43-_ldm_) bits. Then, the pure embedding rate (_PER_) can be defined as:  
\[PER=\frac{Cap-43-l_{clm}}{H\times W} \tag{16}\]  
For each image, the maximum _PER_ is determined by the value of \(m\) and \(T\). In the proposed method, we use the parameter \(T\) to select the smooth pixels, and only the smooth pixels are predicted to choose the embeddable pixels. It is well-known that there are more smooth pixels and more embeddable pixels for the larger value of \(T\). Meanwhile, it will generate more pixels in \(I_{W}^{*}\) which are marked by the location map. The compressed location map is embedded into the edged pixels which is finite. Therefore, it is necessary to ensure that these edged pixels can accommodate the compressed location map and other auxiliary information. The number of edged pixels is 2043 and there are 16,344 bits which can accommodate auxiliary information. Thus, the following condition must be satisfied:  
\[43+l_{clm}\leq 16344 \tag{17}\]  
On the other hand, the value of \(m\) determines bit number that an embeddable pixel can accommodate. The smaller the \(m\), the more data bits can be embedded into an embeddable pixel; however, the pixels that satisfy the embeddable condition would be fewer (i.e., Equation (3)).  
From what has been discussed above, in order to obtain the maximum _PER_ of an image, an optimal combination (_m_, _T_) need to be chosen. For each value of \(m\) (i.e., 3, 4, 5, 6, 7), the value of \(T\) gradually increases from a sufficiently small value of 1 to 50 at most with step size of 1 until the Equation (17) is not satisfied. For each combination (_m_, _T_) that satisfies Equation (17), we can obtain the _PER_ by using Equation (16). Finally, we select an optimal combination (_m_, _T_) to achieve the maximum _PER_ of an image.