esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Preliminaries
\(Enc\) _is a probabilistic encryption algorithm that requires key_ \(K\) _and plaintext_ \(m\in\{0,1\}^{*}\)_, and outputs a ciphertext_ \(c\)_._
3. \(Dec\) _is a deterministic decryption that inputs key_ \(K\) _and ciphertext_ \(c\)_. The output of_ \(Dec\) _is the plaintext_ \(m\)_._  
A physical unclonable function (PUF) is a one-way function implanted in hardware components. The output of the PUF depends on small random deviations that occur during the manufacturing process of the chip. It means that, when queried with the same challenge multiple times, the outcome of the PUF may differ slightly due to environmental and operational factors, such as ambient temperature and terminal voltages. However, fuzzy extractors can eliminate divergences and convert them into deterministic functions [24; 25]. PUFs can be used for hardware authentication and secure key generation for IoT security due to their robustness against physical and invasive attacks and their ability to retain keys without storing them. The blockchain is a decentralized and distributed database system whose primary goal is to eliminate and minimize the involvement of a trusted third-party. By utilizing cryptographic primitives, the blockchain ensures that the inserted data are immutable and the history of the data has not been changed. The distributed nature of the blockchains provides greater availability. **Definition 5**. : _Blockchain is a peer-to-peer distributed ledger that is cryptographically secure, append-only, immutable, and updateable only via consensus or agreement among peers [26]._  
Private blockchains assure the secrecy of the data stored. Although various blockchains differ in handling and building blocks, their structures are similar. Each block has a unique header, and its block header hash value can identify it. Additionally, each block's header stores the previous hash, meaning an attacker must modify the entire chain to change a block's content. The hash function's avalanche effect and the one-way property are vital aspects of the proof of immutability. Ethereum (ETH) is a blockchain platform that was launched in 2015 ([27]). It is open-source and allows for the design and execution of distributed applications through the use of smart contracts, which are Turing-complete programs.
## 2 Unsafe Behavior Identification Model
### Improved YOLOv5s Model Construction
#### 2.2.2 Introducing the CA Mechanism  
The original YOLOv5 architecture uses a comparatively simplistic network structure, exhibiting constrained feature extraction capabilities in complex scenarios that fail to satisfy the demanding detection requirements of construction environments with clutteredbackgrounds. By integrating the Coordinate Attention (CA) mechanism between the neck and head layers, the enhanced model effectively harnesses multi-scale feature maps to strengthen discriminative feature representation, thereby achieving more precise and context-adaptive object detection performance [26]. The CA mechanism can convert any intermediate feature tensor in the model network into a tensor of the same size for output:  
\[X=[x_{1},x_{2},\ldots,x_{c}]\in R^{H\times W\times C} \tag{6}\]  
\[Y=[y_{1},y_{2},\ldots,y_{c}]\in R^{H\times W\times C} \tag{7}\]  
This study integrated the Coordinate Attention (CA) mechanism based on four design rationales:  
1. Occlusion handling: To address the prevalent occlusion challenges in construction scenarios, the CA mechanism selectively prioritizes visible target regions, thereby enhancing model robustness against partial visibility.
2. Global context use: The CA mechanism establishes global contextual dependencies across feature maps, enabling effective integration of site-wide spatial information critical for large-scale construction environments.
3. Spatial dependency modeling: Given YOLOv5's dense object detection requirements, the CA mechanism explicitly encodes inter-regional spatial relationships, significantly improving fine-grained localization accuracy for small/densely distributed targets.
4. Feature discriminability enhancement: Through adaptive feature recalibration, the CA mechanism dynamically emphasizes task-relevant patterns, systematically boosting the network's representational capacity for construction safety monitoring.  
The CA block outperforms conventional SE and CBAM through direction-aware encoding, where by decomposing channel attention into horizontal/vertical feature aggregation, CA improves the localization accuracy of security device detection in cluttered backgrounds, and hardware efficiency, where CA's 1 \(\times\) 1 convolutions add only 0.78 GFLOPs versus CBAM's 1.42 GFLOPs, critical for maintaining 60+ FPS on edge devices.  
An example of the CA mechanism module is shown in Figure 2.  
Figure 2: Example of the CA mechanism module.
## 4 Experiments and Discussion
### Real Image Experimental Results and Discussion
#### 4.2.3 Computation Time  
Table 4 compares the computation times taken for different methods to process a \(1024\times 1024\) test image. Image processing was undertaken in MATLAB R2020b on a PC computer with an i5-9400f CPU (2.90 GHz) and 16 GB of main memory.  
Although the computation time of the proposed IBSGM method was higher due to the self-adaptation process, the corresponding accuracy of nonuniform background elimination and target retention were greatly improved, which is exactly what is required for target recognition.
## Abbreviations  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} DAG & Directed acyclic graph \\ DPAP & Directed path allocation problem \\ V-DPAP & Vertex-constrained DPAP \\ R-DPAP & Resource-constrained DPAP \\ PADAG & Path allocation in directed acyclic graph \\ ILP & Integer linear programming \\ MILP & Mixed integer linear programming \\ POI & Point of interest \\ RT & Request time \\ lex & Leximin solver \\ a-lex & Approximate leximin solver \\ greedy & Greedy solver \\ util & Utilitarian MILP solver \\ p-rr & Path round-robin solver \\ n-rr & Node round-robin solver \\ \end{tabular}  
Notes
* 1 A Nash equilibrium is an allocation in which the modification of a path for a single agent does not improve its associated utility.
* 2 We have removed the worst 5% of values and the best 5% of values for the indicated range.
## 1 Introduction  
Joint stiffness is a condition in which the movement of a joint is difficult or limited in a way that is not caused by weakness or pain [1]. This condition affects the patient's daily life by requiring more effort or force to perform the movement. Usually, joint stiffness occurs after surgery or prolonged immobilization [2]. It is one of the major problems for orthopedic patients. Physical therapies such as joint range exercise or joint rehabilitation play an important role in helping patients to prevent and relieve joint stiffness [3, 4, 5]. Range of motion (ROM) assessment is the most commonly used method to assess the effectiveness of joint motion and measure the distances and directions that a joint can move [6, 7]. Medical usage of ROM includes assisting in the diagnosis, monitoring symptoms, or following up on the treatment of orthopedic diseases [8, 9].  
A goniometer is a standard device for the measurement of wrist ROM [10, 11, 12, 13, 14]. However, a trained staff is required to accurately measure the ROM using the device [15, 16].  
With the advancement of technology and smart devices, the use of a gyroscope for home physiotherapy and an outpatient setting has been explored by many research teams [13; 17; 18; 19]. As of now, a gyroscope is usually integrated into a smartphone and is accessible via an application, making it an easy-to-use and viable option for patients [20]. However, measuring the wrist ROM by using a smartphone could be troublesome and inaccurate in some movements because the smartphone needs to be fixed securely to the wrist [13; 21].  
The objective of this study is to develop a glove embedded with a six-axis inertial measurement unit (IMU) and assess an agreement between the developed device, smartphone, and standard goniometer for the measurement of wrist ROM. The proposed IMU glove is easier and more convenient to use than a goniometer and suitable for any wrist movements in comparison to the smartphone device. In this study, we focus on the wrist joint movements in several motion patterns in all three axes including flexion, extension, supination, pronation, ulnar deviation, and radial deviation, [8; 13].  
The contributions of this study are as follows: (1) development of the glove embedded with IMU; (2) comparison of the measurements of wrist flexion, wrist extension, ulnar deviation, radial deviation, supination, and pronation between goniometer, smartphone, and IMU glove; (3) comparison of intraclass correlation coefficient (ICC) for smartphone and the proposed IMU glove with the goniometer as the gold standard; and (4) comparison of the ICC between different levels of expertise for the three devices.
# Recent Advances in Tunable External Cavity Diode Lasers
## 5 Conclusions  
External cavity semiconductor lasers are characterized by their simple structure and the ability to achieve tunability across different wavelength bands by employing various laser light sources. In this paper, the focus is on three types of external cavity semiconductor lasers. Quantum well lasers, benefiting from mature fabrication technologies, enable external cavity designs that can achieve ultra-narrow linewidth and higher output power. External cavity quantum dot lasers offer a wider tuning range, attributed to the size fluctuation of quantum dots. Meanwhile, external cavity quantum dot lasers have a lower threshold current due to the ground state of QD being more easily saturated. Dual-wavelength tunable lasers, as a significant category of external cavity semiconductor lasers, are also addressed. The relationship between external cavity structure and parameters and the performance of external cavity diode lasers is also discussed. Through the rational design of external cavity structures, it is possible to achieve tunable dual-wavelength output. At present, the external cavity semiconductor laser has excellent performance. With the continuous optimization of performance, it will have better application prospects in the future.  
Conceptualization, Y.W. and Y.S.; formal analysis, Y.W.; investigation, Y.W. and Y.S.; writing--original draft preparation, Y.W.; writing--review and editing, Y.S. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Science and Technology Development Project of Jilin Province [Grant No. 20220201072 GX]; National Natural Science Foundation of China, grant number 62004132; the Doctoral Research Project of Shenyang Normal University, grant number BS202026; the Science and Technology Project of Tianjin [Grant No. 24 YFYSHZ00250].  
Not applicable.  
The authors would like to thank [PERSON] for his contribution in obtaining copyright and polishing the paper.  
The authors declare no conflicts of interest.  
The acronyms used in the manuscript.  
\begin{tabular}{l l} Acronyms & Full Name \\ ECDL & external cavity diode laser \\ DFB & distributed feedback \\ DBR & distributed Bragg reflector \\ VCSEL & vertical cavity surface emitting laser \\ EL & electroluminescence \\ VBG & volume Bragg grating \\ LP-MOCVD & low-pressure metal-organic chemical vapor deposition \\ TEC & thermoelectric cooling \\ AFFF & all-dielectric thin film Fabry-Perot filter \\ ECQDL & external cavity quantum dot laser \\ QD & quantum dot \\ EC & external-cavity \\ AR & anti-reflection \\ HR & high-reflection \\ THz & terahertz \\ \end{tabular}
## 4 Discussion
The interaction between the aforementioned factors was less significant for the 24 h DC values, and the difference between them was smaller, showing that the 24 h DC values were more material dependent, and that the presence of the bracket and choice of curing protocol had a similar effect. The short-term DC values appeared to be more sensitive, reflecting a greater influence of external factors such as bracket or curing protocol. While these factors also affected the 24 h DC values, they may be compensated over time due to the nature of the polymerization reaction and certain specific components within the material. The highest difference in DC values between curing protocols was in the MBG, 5.9% for short-term DC measurements and 4.7% for 24 h measurements. Part of the difference was due to the presence of the bracket during curing. Given that the tested materials do not incorporate specific compositional adjustments that would benefit rapid polymerization, and that the obtained DC values attained using rapid high-intensity curing were significantly lower, a clinician inclined to use rapid curing protocols on modern LED LCUs can be advised to use more highly filled materials as it appears that these are less affected by negative effects of rapid polymerization. Lower DC values can lead to deterioration in material's mechanical properties and the development of caries, and they are also associated with reduced bond strength and more frequent debonding of brackets from the tooth surface [54,55]. Although statistically significant, the clinical relevance of differences in DC < 5% remains uncertain and may not impact the clinical performance of the material to a significant extent. Since this in vitro study was focused exclusively on DC as a fundamental parameter, its main limitations include the absence of bond strength and mechanical testing after simulated aging. These properties should be tested in a follow-up study. Since rapid light curing negatively affected DC, future studies should examine whether the small, but statistically significant, reduction in DC values observed in our study translates into meaningful reductions of mechanical properties, (flexural properties and bond strength to enamel) as well as biological properties, including elution of residual monomers and cytotoxicity.
## 2 Architecture
### M2M Gateway Open Service Interface  
Remote wireless monitoring for district central heating network is not only can obtain the data from the wireless sensor network using a REST-style API, but also capable of wireless sensor network device control and management via REST-style API, making the physical device loosely coupled. Here, we apply the RESTful design guidelines to define some additional API set to monitor and control the physical devices and instruments in heating exchange station and boiler rooms. Figure 5 summarizes the detailed specification of which methods are allowed for each resource.  
Here, we present some monitoring and control automation scenarios of the proposed RESTful APIs. The majority of service requests for controlling and monitoring the devices can be handled in a single invocation:  
_Control list of available devices_, an operator can control the list of available physical devices sending a GET request to retrieve the list of possible configurations and use this information in order to access each context (URI: /Resource/<id>).  
_Access the current setting of a device_, the parameters of a device represents the current setting of a device. The list can be retrieved using a GET request to /Resource/<id>/Device/<id>/Parameters where /Device/<id> identify a device with configuration /Resource/<id>/.  
_Find devices list_, assuming that the URI /Resource/<id>/device/<id> represents the device supervisor, the list of controlled sensors can be retrieved using a GET request to /Resource/<id>/Device/<id>/ that return the list of URIs identifying the devices controlled by the supervisor.  
_Find commands of given device_, the URI /Resource/<id>/Device/<id>/ addresses the device that we want to use. We can retrieve the list of available commands sending a GET request at the URI /Resource/<id>/Device/<id>/Command/.  
_Execute control command_, we can execute a measurement command sending a POST request at the URI / Resource /<id>/Device/<id>/Command/measure the results of the measure can be fetched sending a GET request to the URI/ Resource /<id>/Device/<id>/Attributes/<id>.  
Figure 5: REST API for monitoring and controlling devices.
# Text Normalization Using Encoder-Decoder Networks Based on the Causal Feature Extractor
## 3 Experimental Results
### Second Experiment  
The objective of the second experiment is to compare the four encoders in a more complex scenario, where the samples were selected with more varied sizes. The number of samples of the training, test and validation datasets is the same as in the first experiment, but the samples are randomly selected from the whole dataset, with sizes varying at random between 1 and 177 characters (the maximum allowed length of the output, as justified in Section 2.1).  
As before, Table 6 presents the accuracy measures obtained by the four encoders for the second experiment. Figure 10 and Table 7 show the evolution of the validation error and the results of the statistical tests, respectively.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & & **Test** & \multicolumn{3}{c}{**Validation**} \\ \hline
**Encoder** & **NLLLoss** & **CER (\%)** & **Acc (\%)** & **No. Iters** & **Rate** \\ \hline LSTM & 3.310 & 25.59 & 71.06 & 8900 & 0.206 \\ FCNN & 5.396 & 82.09 & 17.90 & 17 750 & 0.411 \\ FE & 2.680 & 11.93 & 83.38 & 36 650 & 0.848 \\ CFE & 2.686 & 12.69 & 83.45 & 36 200 & 0.838 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Results obtained by the four models for the second experiment (E2). Encoder: Name of the encoder used. NLLLoss: Negative log-likelihood loss. CER: Character error rate. Acc (%): Accuracy. No. iters: Number of iterations. Rate: Iterations per second.  
Figure 9: Evolution of the validation error (NLLLoss) during training of the four models on E1.  
Again, FE and CFE are the two best encoders, being able to achieve an accuracy above 83.3%, while LSTM only obtains a 71%. Moreover, FCNN is unable to function properly, with a poor 17.9%. In fact, all the performance measures of FE and CFE are very close, and so are their computational efficiencies. However, the statistical test, which is performed on the accuracy parameter, proves that CFE is significantly better than FE; the probability that they are indistinguishable is only 0.03%. Overall, the obtained results indicate that this experiment is far more complex than E1, which had a best accuracy of 96.8%. Moreover, the training time in E2 is 12 h, while it was only 1 h for E1. Figure 10 suggests that LSTM would need even more time to reach convergence; it not only performs fewer iterations per second, but it requires more iterations to converge.
## 5 Experiment and Discussion
### Experiment Result and Discussion  
#### 5.3.1 Node Classification Task  
First, we verified the node classification task, and the experimental results are shown in Table 2. We mark our results in bold and underline the best results (the same below). As it can be seen from Table 2, comparing the results of the MRDE method on DBLP and IMDB, it can be found that the classification effect of the MRDE method in this paper is improved on both datasets (the highest on DBLP is increased by 30%, and the lowest is increased by 0.7%. The highest increase is 41.8% on IMDB, and the lowest is 0.5%), which fully reflects the necessity of introducing local graph embedding and attention balance mechanism when considering multiple adjacency matrices with different structures at the same time.  
In addition, for DBLP and IMDB, the JUST, CTDNE, and C2V methods, which are based on DHINs, are better than static methods (GCN, GAT, M2V), it shows the effectiveness of the DHIN methods, and also verifies the implicit assumption of mining semantic information and temporal information in HINs is beneficial to improve the quality of node representation. At the same time, we also compared the Raw method (input features are directly used as node representations), and we can find that the Raw method has a poor processing effect compared with each other method, thus excluding the possibility that the input features lead to better performance of the model.  
Similarly, compared with M2V, which only uses the semantic relation network structure for representation learning, the HIN embedding methods, which effectively combine the input features and structural information, can usually obtain better node representation.  
In addition, in the IMDB dataset, the effectiveness of MRDE is worse than that in DBLP. We analyze and find that the target nodes in the IMDB dataset are often weakly correlated; for example, the same director may direct different types of movies, while the same actor may also appear in different types of movies, thus introducing more noise.
# Bi-Stability in Flexure Beams: Introducing a Setup for Experimental Characterization
###### Abstract  
Bi-stable mechanisms can remain in two positions without a power input or locking system. These mechanisms can achieve large displacements with low energy, requiring power only during switching. However, their design and analysis are challenging due to the non-linear behavior of their flexible members. Researchers commonly use experimental approaches to study and validate bi-stability, which demands efficient and affordable setups. This work presents a versatile and easy-to-fabricate setup to investigate the bi-stable behavior of flexure beams made of styrene plastic. The testing setup is made of laser-cut acrylic connectors and 3D-printed fixtures. The experiments demonstrate that all tested beams are bi-stable and highlight the impact of thickness on their behavior. The critical forces obtained range from 0.0277 N to 5.2724 N between the thinnest and the thickest samples. The distance traveled before snapping increments, with thickness, ranges from 18.78 mm to 32.6 mm. The samples were subjected to a cyclic compressive load and demonstrated a considerable decrement in the critical forces after the first load. Thicker flexural beams present a more significant deformation, causing fractures in some cases after the five loads. Regardless of the thickness, all samples traveled the same total linear displacement of 45 mm. The presented setup demonstrated consistency and rapidness in experimental bi-stability characterization, with the styrene plastic flexure beams proving to be suitable for studying bi-stability.  
flexure beams; bi-stable mechanism; experimental setup +
Footnote †: journal: Applied Sciences