esa-sceva/satcom-chunk-collection huggingface dataset:
# An IoT-Based Participatory Antitheft System for Public Safety Enhancement in Smart Cities
## 3 Methods and Materials
### Mobile Phone Application Features  
In many cases, a smartphone is used to inform its owner for an event detected by an IoT device [44]. In our study, the mobile phone application includes specific functionalities relevant to theft detection scenario. These functions were mapped to distinct buttons on the mobile app user interface (UI) encompassing certain operational features. The following options are available:  
* Tag register;  
Figure 5: Antitheft tag workflow chart.  
Tag deregister;
* Theft report;
* Stealth mode on;
* Activate my device.  
Tag Register option is used in order to have the tag registered. Various registration methods can be used. For instance, the QR (Quick Response) code is read and next is decoded it into JWT (Jason Web Tokens) format. Then, the user places the battery to power up the sensor tag which normally switches to advertisement mode.  
The user, via a password established connection, can put the device into deactivated or stealth mode. Afterwards, the user may initialize the rediscover process tag for at least three seconds. If the tag cannot be detected, it means that it has been switched to receive mode; therefore, it consequently broadcasts no signal at all. Then, the user can reactivate the tag (using the Activate my Device button) and try to discover it. This time the tag should be active and visible. The process is considered to be completed, and the user can proceed to finalizing the tag registration and association with user identity via the City.Risks platform.  
To deregister the tag, the user should activate the tag and scan for it to ensure that the tag cannot be deregistered again by another user. Afterwards, the user can deregister the tag via the City.Risks platform and, if required, re-register the unit again.  
Theft Report button should be used by the end user in order to report a theft incident to the City.Risks Operation center. In order to facilitate the retrieval process the user -should also report the location of the item's last known position and the time data. Therefore, location and time related stamp tokens will also be transmitted to the City.Risks authorities.  
The REST endpoint in the Operation Center will notify the mobile application that there are stolen devices in the area. The notification method is based on the JSON/GET method [45].  
Next, the mobile app requests the required items from the REST endpoint. Again, only stolen BLE tags are received by the app and are stored locally in the app's database. Figure 6 illustrates the aforementioned approach.  
The mobile app then starts advertising processes to activate inactive BLEs listed in the database file. Additionally, it starts the scanning process to pinpoint active BLEs listed in the database file. Once a BLE tag is received, the mobile app sends the scanned device to the relevant web service structure data using the POST method [45].
# Bonded-Particle Model with Nonlinear Elastic Tensile Stiffness for Rock-Like Materials
## 4 Application of the NET-BPM
### Modelling LDB Granite  
A rock specimen with the size same as that in [42] is created using the method in [44] with \(R_{max}=0.9\) mm and \(R_{min}=0.3\) mm. The effect of particle size is not discussed in this study, so the particle size same as that in Section 3 is adopted. The parameters of the specimen for LDB granite are listed in Table 4. The properties of the LDB granite are presented in Table 5, where [PERSON]'s modulus are from [49], and the rest of the data are from [42]. It should be noticed that [PERSON]'s modulus and [PERSON]'s ratio are converted to the apparent values.  
From the investigation in Section 3, we know that \(b\) is the major factor affecting the values of \(E_{c}/E_{t}\), and that \(b\) and \(k_{s}/k_{n}\) is the major factor affecting the values of \(v_{c}\). Combining Figures 9b and 11c,d, the values of \(b\) and \(k_{s}/k_{n}\) can be roughly estimated to satisfy that \(v_{c}=0.35\) and \(E_{c}/E_{t}=1.43\). Then \(k_{n}\) can be estimated by amplifying initial value in Section 3 to obtain that \(E_{c}=68.1\) GPa. The next step is to get an appropriate value of \(e_{0}^{n}\) so that TS = 9.3 MPa is obtained. The last step is to guarantee that UCS = 200 MPa, which can be achieved by choosing proper values of \(k_{m}/(k_{n}R)\), \(w\) and \(e_{0}^{s}/e_{0}^{n}\). Proper micro parameters in NET-BPM for LDB granite can be obtained through several simulations and modifications, as shown in Table 6. The macro parameters obtained are presented in Table 5.  
As the ultimate axial strain in tensile test is small, a lower loading speed of 0.01 m/s is applied in direct tensile tests. The results show that not only \(E_{c}\), \(v_{c}\), UCS, TS and UCS/TS from the NET-BPM model are in good agreement with the experimental values, which is achieved in [14], but also \(E_{t}\) and \(E_{c}/E_{t}\) are in good agreement with the experimental values. The stress-strain curves of the LDB granite under uniaxial compression test from our method are similar to those from experiments in [42], as shown in Figure 14. The crack patterns of LDB granite under compression and tension tests are shown in Figure 15. Same method introduced in Section 2.4 is used to present the cracks. Figure 15a shows the cracks at the time when the compressive load reaches its peak. After that, the cracks develop quickly. Most of them are oblique. Figure 15d shows the cracks at time when the tensile load reaches its peak. The cracks extend perpendicular to the loading direction quickly, which results in the fracture of the specimen.
# Quantum Computing for Healthcare: A Review
## 6 Security of Quantum Computing for Healthcare
### Semiquantum Key Distribution  
SQKD exploits novel quantum capabilities of at least one party in communication. It eliminates computational overhead and alleviates computational cost. SQKD ensures that both ends of the communication achieve QKD. In this mechanism, only the sender should be quantum-capable, whereas the receiver may have classical capabilities. Specifically, the sender performs various operations, including preparation of quantum states, performing quantum measurements, and storage of quantum states. In this paradigm, the receiver performs multiple operations, including preparation of novel qubits, measurement of qubits, order arrangement of qubits, and transmitting qubits without disturbing quantum channels. [PERSON] et al. [172] proposed the first SQKD in 2007. In this scheme, they used single photons to determine the robustness of the protocol. In the later state, they extended this work by generalizing the underlying conditions. They analyzed these conditions and proved that complete robustness could only be achieved when the qubits are transmitted individually but are attacked collectively. In their later work, [PERSON] et al. [173] also proposed a feasible protocol using four-level systems. [PERSON] et al. [174] proposed a classical sender-based protocol. The sender can send encoded key bits on a Z basis. [PERSON] et al. [175] proposed a robust SQKD protocol that transfers fewer than four quantum states. [PERSON] et al. [176] analyzed a two-way eavesdropping scheme against an SQKD protocol. [PERSON] et al. [177] proposed a secret key-sharing scheme between two classical users. In [178], the authors avoided measurement capabilities of the sender and ensured that it is robust against joint attacks, thus showing that the measurement capability of the classical users is not essential for the implementation of SQKD. [PERSON] et al. [179] used an untrusted quantum server that tries to steal session keys. Currently, various quantum states and technologies are used to devise novel protocols [180; 181; 182; 183; 184; 185]. Additionally, a few researchers have analyzed the security vulnerabilities of SQKD [186; 187; 188]. The taxonomy and summary of research studies focused on leveraging SQKD is presented in Table 9.
## 4 The Global SAC and Grid Systems
### The Icosahedron Version of the Global Grid System  
The last version of SACs that we propose is based on the icosahedron. In this paragraph, we provide some visual examples of the icosahedron version of the global grid system and do not deduce the equations of the transformation again. The icosahedron orientation is as follows:  
\[\begin{array}{ll}V_{1}=(0,0,1);&V_{2}=(0,\frac{a}{2\sin(2\alpha)},z);\\ V_{3}=(\frac{a}{4\sin^{\prime}}-\frac{a}{4\cos^{\prime}a},z);&V_{4}=(-\frac{a}{ 2},-\frac{3-4\sin^{2}a}{4\cos\alpha}a,z);\\ V_{5}=(\frac{a}{2},-\frac{3-4\sin^{2}a}{4\cos\alpha},z);&V_{6}=(\frac{a}{4\sin \alpha},\frac{a}{4\cos\alpha},z);\\ V_{7}=(-\frac{a}{2},\frac{3-4\sin^{2}a}{4\cos\alpha}a,-z);&V-8=(-\frac{a}{4 \sin^{\prime}},-\frac{a}{4\cos\alpha},-z);\\ V_{9}=(0,-\frac{a}{2\sin(2\alpha)},-z);&V_{10}=(\frac{a}{4\sin\alpha},-\frac{ a}{4\cos\alpha},-2);\\ V_{11}=(-\frac{a}{2},\frac{3-4\sin^{2}a}{4\cos\alpha}a,-z);&V_{12}=(0,0,-1) \end{array},\]  
where  
\[z1=\sqrt{1-\frac{4}{(10+2\sqrt{5})\sin(\frac{\pi}{5})^{2}}};\quad a=\frac{4}{ \sqrt{10+2\sqrt{5}}};\quad a=\frac{\pi}{10}.\]  
We define the icosahedron version of SACs with four components \(\lambda_{i},i=1,2,3,4\). The first three components are the coordinates of the spherical point, and the last component denotes the region to which the point belongs, that is, region \(\lambda_{4}\in\{1\ldots 20\}\) (in Figure 14). Figure 15 illustrates three levels of DGGSs that are based on these coordinates.
# Multi-Path Data Distribution Mechanism Based on RPL for Energy Consumption and Time Delay
## 3 Adaptive Multipath Traffic Loading Based on RPL, AMTL-RPL
### Energy Balance Based on the RPL  
The first concern is the energy balance of the network. According to the idea of multipath transmission, in order to ensure the residual energy balance of the subsequent nodes, the sending node will transmit its data through multiple paths. This method will lead to multiple bottleneck nodes in the network, and makes it necessary to maintain the information of multiple bottleneck nodes. This section describes how to calculate the residual energy of the bottleneck node and how to allocate its transmission traffic. Specifically, we first analyze the basic energy consumption of the node, and then according to the Pareto evaluation model [30] to provide a measurement of the node's energy distribution. Afterwards, we analyze the node's energy consumption situation based on multipath distribution and finally propose the best plan for traffic distribution.
# File-YOLO: A Faster, Lighter, and More Efficient Strategy for Autonomous Tower Crane Hook Detection
## 5 Experimental Results and Discussion
### Comparative Analysis of Experimental Results
#### 5.2.2 Performance Comparison of Different Networks
Compared with other most advanced algorithms of the same order within the YOLO series, including YOLOv9s, YOLOv10s, YOLOv11s, and YOLOv12s, the FLE-YOLO algorithm shows the best performance in terms of precision, AP\({}_{50}\), and FLOPs. The P has increased by 0.7%, 0.3%, 1.1%, and 2.2%, while the mAP\({}_{50}\) has increased by 3.1%, 1.2%, 1.9%, and 2.3%. The FLOPs, which measure model complexity, decreased by 7.3 G, 2 G, 1.9 G, and 1.8 G, respectively. This demonstrates that the FLE-YOLO algorithm performs well in tower crane hook detection with lower model complexity. Compared to the best algorithms in this series, other metrics show only minor differences, indicating high practicality and applicability. Given that the dataset used in this study is a single category crane hook dataset, the improved network exhibited significant enhancements in both detection performance and lightweight design. Real-time and effective detection of the hook in the frame provides \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Model** & **Backbone** & **P** & **mAP\({}_{50}\)** & **FPS** & **FLOPs/G** & **Parameters/M** \\ \hline YOLOv3-spp & Darknet-53 & 0.949 & 0.945 & 29.069 & 293.1 & 104.71 \\ YOLOv5s & CSP-Darknet-53 & 0.957 & 0.935 & 101.01 & 23.8 & 9.112 \\ YOLOv6s & RepVGG & 0.966 & 0.946 & 62.5 & 44 & 16.297 \\ YOLOv8s & C2f-sppf- & 0.973 & 0.977 & 95.238 & 28.4 & 11.125 \\ YOLOv9s & GELAN & 0.966 & 0.952 & 136.986 & 26.7 & **7.167** \\ YOLOv10s & CSP-Darknet-53 & 0.970 & 0.971 & **208.333** & 21.4 & 7.218 \\ YOLOv11s & C3K2 & 0.962 & 0.964 & 161.29 & 21.3 & 9.413 \\ YOLOv12s & R-ELAN & 0.951 & 0.960 & 147.058 & 21.2 & 9.231 \\ FLE-YOLO & FasterNet & **0.973** & **0.983** & 142.857 & **19.4** & 7.588 \\ \hline \hline \end{tabular} Note: The bold data represents the optimal values.  
\end{table} 
Table 5: Results Comparison of Ablation Experiments. accurate two-dimensional positioning coordinates for the camera gimbal, ensuring effective tracking of the hook from the remote-control room.
# Binary Mixes of Self-Compacting Concrete with Municipal Solid Waste Incinerator Bottom Ash
###### Abstract  
With the objective of establishing a viable alternative to the use of cement, the main objective of this study is to verify the possibility of using municipal solid waste incinerator bottom ash (MIBA) as a partial cement replacement, thereby reducing the environmental impact associated with the use of concrete as a building material. To this end, self-compacting concrete (SCC) binary mixes of cement and MIBA were evaluated in their fresh and hardened state (i.e., self-compactability, mechanical and durability related performance). Four SCC mixes were produced to cover a wide range of replacement levels of cement with MIBA, namely: 20%, 30%, 40% and 50%. A fifth SCC mix, without MIBA, was produced with 30% fly ash to carry out a comparative analysis with composites with well-established performance. The results showed that the use of bottom ash from municipal solid waste incinerators caused an overall decline in the performance of self-compacting concrete. Apart from the smaller number of reactive phases in the bottom ash when compared with fly ash, which led to a slower rate of strength development, the decline was also caused by the increased porosity from the oxidation of aluminium particles. Nevertheless, the results showed promising indicators regarding the durability of mixes with 20% MIBA, with values very similar to those of reference concrete.  
self-compacting concrete; municipal solid waste; incineration; bottom ash; fresh properties; mechanical properties; durability +
Footnote †: journal: Applied Sciences
# Zero-Shot Image Classification with Rectified Embedding Vectors Using a Caption Generator
## 1 Introduction
This generated-text-feature vector is combined with the original image-feature vector. Therefore, this rectified vector has a better representation on joint-embedding space, which leads to improved classification performance when it is compared with prototype vectors composed of free-style textual sentences. In summary, the main contributions of this work are as follows:  
* We propose a novel approach for zero-shot image classification using additional semantic information generated from an image-caption generator. Unlike [17,18] studies that have used the caption generator for enhancing visual feature extraction, the proposed model directly uses the generated text information for the rectification of the embedding vector in the semantic space. * The generated-text-feature vector enhanced the image-embedding vector in the testing stage by providing additional information. We call this vector a rectified vector, and it exhibits significant improvement in classification accuracy through the experiments. * We also demonstrate that image-caption generators can play an augmentation role in learning a joint-embedding space, especially when the image-description pairs in the training set are insufficient. The paper is organized as follows. In Section 1, we describe the zero-shot image classification problem and briefly explain the existing prototype-based methods with a limitation and our proposed approach to solve it. In Section 2, the related works, zero-shot image classification, and image captioning are described. In Section 3, the proposed method for rectifying embedding vectors and data augmentation using generated captions are explained. In Section 4, we analyze the quantitative and qualitative results of the proposed method on two benchmark data. Finally, in Section 5, a summary and future work are presented.
# SLMAS: A Secure and Light Weight Mutual Authentication Scheme for the Smart Wheelchair
### Key Terms Explanation
#### 1.1.5 Asymmetric Cryptography  
Information is encrypted via a public key and decrypted via a private key in asymmetric cryptography. This makes it possible for two people to communicate securely without revealing the secret key. Asymmetric cryptography is frequently used in various applications, such as secure email, online banking, and e-commerce, as well as for digital signatures, key exchange, and encryption.
###### Abstract  
Transducer arrays are commonly analyzed by the finite element method (FEM) with high accuracy, but it is costly, particularly when having flexible surrounding structures. In this study, we developed an equivalent circuit (EC)-based model of an array of transducers with flexible surrounding structures for effective analysis. The impedance matrix was first constructed by coupling the electrical, mechanical impedance, and the acoustic radiation impedance obtained by the EC method and finite element-boundary element (FE-BE) coupling method. The transfer matrix of far-field pressure to the transducer response was then constructed by the FE-BE coupling method, and finally the sound pressure of the external acoustic field was obtained. To verify the accuracy, the results of the proposed method were compared with those of the conventional FEM. To evaluate the efficiency of the proposed method, the reduction in the degrees of freedom (DOFs) of the proposed method from the conventional FEM analysis was investigated. The simulation results of the proposed method are highly accurate and efficient. The proposed method is expected to be useful for conceptual design.  
transducer array; equivalent circuit; finite element-boundary element coupling method; multi-physics system; phased array Article
## 3 Experiments
### Data Preprocessing  
During the acquisition process, ECG signals are subject to three types of noise such as myoelectric interference, baseline drift, and power line interference. Wavelet transform has a good effect on eliminating the above three kinds of ubiquitous noises in ECG signals. This paper used the wavelet transform method proposed in [16] to filter the original ECG noise, and utilized Daubechies D6 ('db6') wavelet basis function to decompose the ECG signals to 10 levels. Table 1 corresponds to the components of the wavelet transform frequency band of ECG signals. The low and high frequency component are called approximation and detail, respectively. We removed the D1 (250-500 Hz), D2 (125-250 Hz), D3 (62.5-125 Hz) detail components, and the A10 (0-0.4875 Hz) approximation component, and reconstructed the remaining components to obtain signals without noises. Figure 3 shows the heartbeats before and after the noises were removed.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Components** & **Frequency Band (Hz)** & **Components** & **Frequency Band (Hz)** \\ \hline D1 & 250–500 & D7 & 3.9–7.81 \\ D2 & 125–250 & D8 & 1.95–3.9 \\ D3 & 62.5–125 & D9 & 0.975–1.95 \\ D4 & 31.25–62.5 & D10 & 0.4875–0.975 \\ D5 & 15.63–31.25 & A10 & 0–0.4875 \\ D6 & 7.81–15.63 & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: The frequency band of wavelet transform components.  
Figure 3: Heartbeats before and after noises were removed: (**a**) The original ECG signal; (**b**) ECG filtered signal by wavelet transform.  
After the noises were removed, each ECG record was segmented according to a fixed length in consideration of the input characteristics of the CNN. First, we used the Pan-Tompkins algorithm to detect the R-peaks [17], and then the R-peak positions were utilized for heartbeat segmentation. After segmentation, each heartbeat contained 600 sampling points (199 sampling points were selected on the left side of the R peak and 400 sampling points on the right side), and the length of a single heartbeat was 0.6 s, which basically covered the range of a P-QRS-T wave. The amplitude distribution of the normal and myocardial infarction segmentations differed, which would affect the calculation rate. In order to accelerate the calculation effect, the segmented ECG signals were normalized to improve the convergence speed of the model. As shown in Figure 4, there was a clear distinction between the normal ECG and myocardial infarction ECG [18].
# Inertial Parameter Identification in Robotics: A Survey
## 10 Results, Discussion and Perspectives
### Analysis and Discussion of the Results
#### 10.1.2 Estimation Accuracy
It is worth noting that the number of iterations--and hence model recalculation--required by PC-IDIM-IV and PC-DIDIM are similar, in the case of proper convergence, to that of the unconstrained IDIM-IV and DIDIM, respectively. The computation time of CLIE and CLOE is generally about one order of magnitude higher than the unconstrained IDIM-IV and DIDIM, which is not really surprising considering the large number \(E(d_{N_{\mathit{sim}}})\) of DDM simulations required to evaluate the Jacobian at the current estimates (c.f. the different FOM tables). Again, this is consistent with the computation time given in [5]. A careful reader will probably notice that the computation time does not scale linearly with the number of samples, in particular when making use of parallel decimation. This observation is a direct consequence of the fact that model simulation, within IDIM-IV, DIDIM, CLIE, and CLOE is carried out at the controller frequency, namely \(f_{c}=5\) kHz. In the case of CLIE, CLOE, and ML, the sensitivity function in the Levenberg-Marquardt optimization routine can be computed in parallel, thereby further increasing the execution speed. In our case, these computations were distributed on 12 parallel threads, which was made possible thanks to the Matlab parallel computing toolbox. Unlike the other methods, the time taken by the NKF to find a solution scales linearly with the number of samples. In the case of sigma-point Kalman filters, the whole distribution of prior estimates must be propagated through the nonlinear DDM. In our case, considering the set of 52 base parameters and the 12-dimensional robot state vector, a total of 129 sigma-points must be propagated through the DDM at each filter iteration. To speed up the computations, we took the decision to distribute the burden on four different threads. Finally, the sample propagation loop was compiled into a mex file to further accelerate the execution speed. In this manner, the time ratio between an EKF execution and a UKF execution could be reduced to 4.