esa-sceva/satcom-chunk-collection huggingface dataset:
# Safety Control for Satellite Formation Flying via High-Order Control Barrier Functions
## 3 Safety Control Design
### High-Order Control Barrier Function Design
The relative degree of the control barrier function with regard to System (9) is greater than 1. To construct the control barrier function for System (9), define the following functions. \[\dot{x}_{2} = 2\omega x_{4}+\omega^{2}x_{1}-\frac{\mu}{d^{3}}x_{1}+u_{1},\]5 \[\dot{x}_{2} = 2\omega x_{4}+\omega^{2}x_{1}-\frac{\mu}{d^{3}}x_{1}+u_{1},\]6 \[\dot{x}_{2} = 2\omega x_{4}+\omega^{2}x_{1}-\frac{\mu}{d^{3}}x_{1}+u_{1},\]7  
where \(\alpha_{1,i}(\cdot)\) and \(\alpha_{2,i}(\cdot)\) are \(\mathcal{K}\) class functions. Furthermore, the following sets can be defined based on the above functions. \[\dot{x}_{2} = 2\omega x_{4}+\omega^{2}x_{1}-\frac{\mu}{d^{3}}x_{1}+u_{1},\]8 \[\dot{x}_{2} = 2\omega x_{4}+\omega^{2}x_{1}-\frac{\mu}{d^{3}}x_{1}+u_{1},\]9 \[\dot{x}_{3} = x_{4},\]0  
If there exist \(\mathcal{K}\) class functions \(\alpha_{1,j}(\cdot)\) and \(\alpha_{2,j}(\cdot)\) such that \(\mathcal{H}_{2,i}\geq 0\) hold for \(\forall x_{i}\in\bigcup(\mathcal{C}_{0,i}\bigcap\mathcal{C}_{1,i}\bigcap \mathcal{C}_{2,i})\), the function \(h_{i}(x)\) is a second-order differential higher-order barrier function with regard to System (9), and the set \(\bigcup(\mathcal{C}_{0,i}\bigcap\mathcal{C}_{1,i}\bigcap\mathcal{C}_{2,i})\) is forward invariant. For System (9), considering the set \(\bigcup(\mathcal{C}_{0,i}\bigcap\mathcal{C}_{1,i}\bigcap\mathcal{C}_{2,i})\) and the functions \(\mathcal{H}_{0,i}\), \(\mathcal{H}_{1,i}\), \(\mathcal{H}_{2,i}\), if there exist \(\mathcal{K}\) class functions \(\alpha_{1,j}(\cdot)\) and \(\alpha_{2,j}(\cdot)\) satisfying the following inequality:  
\[\dot{x}_{3} = x_{4},\]1 \[\dot{x}_{3} = x_{4},\]2  
where the function \(h_{i}(x)\) is a control barrier. Accordingly, designing a control barrier function \(h_{i}(x)\) for System (9) yields the following safety control input set:  
\[\dot{x}_{3} = x_{4},\]3 \[\dot{x}_{3} = x_{4},\]4
# Exploring the Genetic Basis of Dens Evaginatus Using Whole-Exome Sequencing
## 1 Introduction  
Dens evaginatus (DE) is a dental abnormality that is characterized by a conical or rod-shaped tubercle on the central portion of the occlusal surface of the premolars, especially the second mandibular premolar, and rarely on the third molar [1, 2]. The same abnormalities, when present on the anterior teeth, are referred to as talon cusps and are often seen on the lingual surface [3]. DE is often found bilaterally or symmetrically [4], and the tubercles, on average, are approximately 2 mm wide and 3 mm high [5]. Moreover, the tubercles generally contain dental pulp, which is covered by enamel and dentin [6]. The presence or absence of dental pulp within the tubercles is clinically significant and distinguishes DE from other dental abnormalities, such as a cusp of Carabelli, which does not contain dental pulp [4, 7].  
Since patients with DE frequently experience complications, DE needs to be diagnosed early and treated appropriately. DE tubercles can wear or fracture due to occlusal and functional interference with the opposing teeth. Fractures can result in pulpal and periapical inflammation if the dental pulp is exposed [8]. DE can also cause malocclusion and loosening of the teeth [4, 9]. Temporomandibular joint pain is also noted in some cases due to occlusal trauma associated with DE [8, 10].  
Although the etiology of DE is unclear, the general hypothesis is that DE has a genetic component that affects traits involved in tooth development at the Bell stage [11]. Abnormal proliferation and folding of the inner enamel epithelium and dental papilla are thought to be involved in DE formation [9, 12].  
The prevalence of DE varies widely by race and ethnicity. The incidence of DE is reported to be more common in Asians than in other races, with an incidence rate of approximately 0.5-4.3% [13]. A high incidence of DE has also been reported in Inuit, Alaskan Natives, and American Indians [14,15]. [PERSON] et al. [16] were the first to describe DE and its incidence in Inuit.  
Racial differences are also noted in other developmental anomalies and suggest the possibility of a genetic component; for example, shovel-shaped incisors and mesiodens are common in Asians [6,17]. Hence, developmental tooth abnormalities, including cusp of Carabelli, paramolar cusp, enamel pearl, talon cusp, and shovel-shaped incisors, have been investigated in order to clarify the genetic factors that contribute to their occurrence. Shovel-shaped incisors are associated with a gene variant of _EDAR_ (Ectodysplasin A Receptor), which influences tooth shape and size [18]. Talon cusp has been reported in a family with oculofaciocardiodental syndrome, which is considered to be caused by _BCOR_ (BCL6 Corepressor) [19].  
Although autosomal and X-linked dominant patterns have been proposed for DE [20,21], the genetic factors associated with the development of DE have not been investigated to date. Therefore, the present study investigated the genetic background of DE using whole-exome sequencing (WES).
# Modeling and Resolving Uncertainty in DIKWP Model
## 2 Problem Description
### Uncertainty in Market Conditions
#### 2.1.2 Market Sentiment  
Investors' emotions and expectations can also significantly impact market prices, often based on investors' perceptions rather than actual economic indicators.
* **Market overreaction (\(e_{3}\)):** Market participants may overreact to certain news or events, leading to sharp short-term fluctuations in asset prices that may be unrelated to fundamentals. For example, if the CEO of a large technology company suddenly announces their resignation, even though the long-term impact of this resignation on the company's fundamentals may be limited, the stock price may experience a significant decline in the short term due to market sentiment. High-frequency traders can profit from these short-term price fluctuations by capturing them swiftly after the news is announced, trading based on anticipated systematic model expectations.
* **Unconfirmed news (\(e_{4}\)):** Unconfirmed news or rumors spread on social media and news websites can quickly alter market sentiment, causing short-term fluctuations in the prices of certain assets. For instance, if rumors about the imminent acquisition of a listed company circulate online, even though this news is unconfirmed, the company's stock price may temporarily rise due to investors buying in. High-frequency traders may capitalize on these short-term price movements for trading, but they also face high risks because once the news is confirmed to be false, the stock price may quickly fall back, indicating that precise control over risk assessment is required.
* **Herd behavior (\(e_{5}\)):** Investors may mimic the behavior of other investors rather than make investment decisions based on their analysis, leading to herd behavior in the market, and exacerbating asset price fluctuations. For example, when a particular stock or industry suddenly becomes favored by the market, a large number of investors may follow suit and buy-in, driving up prices. However, this price increase is often not supported by the fundamentals of the company. Once the trend reverses, followers may rush to sell their stocks, causing prices to plummet sharply. High-frequency traders can identify the formation and reversal of such trends through algorithms, thus swiftly entering and exiting the market when market sentiment changes, capturing profits.
# Performance Analysis of Post-Quantum Cryptography Algorithms for Digital Signature
###### Abstract  
In the face of advancing quantum computing capabilities posing significant threats to current cryptographic protocols, the need for post-quantum cryptography has become increasingly urgent. This paper presents a comprehensive analysis of the performance of various post-quantum cryptographic algorithms specifically applied to digital signatures. It focuses on the implementation and performance analysis of selected algorithms, including CRYSTALS-Dilithium, Falcon, and SPHINCS+, using the liboqs library. Performance tests reveal insights into key pair generation, file signing, and signature verification processes. Comparative tests with the well-known and popular RSA algorithm highlight the trade-offs between security and time efficiency. The results can help to select secure and efficient ciphers for specific 5G/6G services.  
post-quantum cryptography; digital signature; cipher; secure services; efficiency +
Footnote †: journal: Applied Sciences  
1
# The Conditional Probability of Correlating East Pacific Earthquakes with NOAA Electron Bursts
## 1 Introduction
This analysis has been recently improved upon by considering the interval of 1.5-3.5 h before strong EQs in the West Pacific and resolving the ambiguity of recognizing EBs without knowing the EQ epicenters a priori [27]. The aim was to develop a methodology for EQ forecasting and verification [28]. Based on the theory of conditional probability developed in past studies [27; 28] for EQ forecasting, an application for both EQ and tsunami risk reductions will be described for seismic activity in the East Pacific. Moreover, Section 2 will describe the databases used for the analysis and their relative restrictions. Section 3 will deal with the selection of EBs used to verify their correlation with East Pacific's strong EQs. This correlation is used for possible risk reduction applications discussed in Section 4, due to a longer time lag of correlated EQs. Finally, a summary of the results is reported in the Conclusions.
# An Energy-Balanced Geographic Routing Algorithm for Mobile Ad Hoc Networks
## 3 Em-Gpsr
### Flow of the EM-GPSR Algorithm  
In terms of the features of EM-GPSR, we extend the HELLO packet format of the GPSR protocol [36], including node ID, position, velocity and remaining lifetime, as shown in Figure 6. Note that the signaling overhead of our algorithm is more than twice that of the most basic hello protocols [37], while our routing performance is greatly improved, at the cost of overhead.  
Figure 4: Energy and mobility greedy perimeter stateless routing (EM-GPSR) candidate set.  
Figure 5: EM-GPSR greedy forwarding.  
The EM-GPSR routing protocol is designed according to the energy balance optimization model. The concrete steps are listed as follows.  
* Step 1: Network initialization, where all nodes periodically send HELLO packets to neighbor nodes.
* Step 2: If node \(i\) receives a HELLO packet from a neighbor node, it checks whether the node ID in the HELLO packet already exists in its local memory.
* Step 3: When the source node \(S\) is ready to transmit data to the destination node \(D\), according to the routing table node state information (movement speed and distance), it selects the candidate set first. Then, according to Equation (9), it further selects the best next-hop node \(c\) from the candidate set and sends the packet to the node \(c\).
* Step 4: The node \(c\) receives the data packet, determines whether it is the destination node, if so, ends the routing process; otherwise, it determines whether the selected region is void, and if not, employs planar forwarding (right-hand rule), otherwise it returns to step 3.  
A flowchart of the EM-GPSR routing protocol is shown in Figure 7.
# Iterative Positioning Algorithm for Indoor Node Based on Distance Correction in WSNs
## 3 Iterative Positioning Algorithm for the Target Node Based on Distance Correction
### The Preprocessing of the Iterative Positioning Algorithm  
Before the design of the iterative positioning algorithm, some pre-processing tasks must be performed. First of all, the mathematical model of the RSSI is constructed and used to calculate the initially measured distance. Then, the influence of noise on the measured distance is analyzed and thereby the noise impact factor is derived. Finally, the triangle centroid positioning algorithm is used to obtain the initial positioning coordinates of the target node.
## 2 Literature Review
### Indoor Positioning Methods of AR-Based Indoor Navigation Systems  
In [33], [PERSON] et al. developed an augmented-reality-based navigation system called ARBIN for indoor navigation. The localization method employed in their work uses Bluetooth RSSI values from Lbeacon placed inside the building. This approach was able to achieve 3-5 m localization accuracy and provide correct instructions to reach destinations.  
However, the need to use Lbeacon for user localization constrains the implementation, making it less scalable due to the requirements for additional Lbeacons and extensive RSSI measurement and mapping in new environments.  
In [34], [PERSON] proposed using \(AR\) markers in an \(AR\)-based smartphone indoor navigation system to help visually impaired people navigate indoor environments. The \(AR\) markers act as guides, requiring the system to scan them incrementally to ensure that the user reaches their destination accurately. The approach achieved results close to the true value during the evaluation. However, implementing \(AR\) markers for user localization hinders scalability and complicates the implementation process, as the markers need to be placed throughout the building.  
In [35], [PERSON] developed a mobile augmented reality system for indoor navigation by utilizing a smartphone's internal sensors. The system employs the IndoorAtlas SDK, which leverages the magnetic field captured by the smartphone sensors and the building's WiFi signal. The localization method achieved an accuracy of around 1.2 m, and the developed system received positive feedback from survey participants. However, utilizing the magnetic field requires mapping the building through fingerprinting, as it is necessary to determine the user's coordinates relative to their current location. When implemented in new buildings or locations, this limits and constrains the system's scalability.
# Novel Sparse-Coded Ambient Backscatter Communication for Massive IoT Connectivity
## 1 Introduction
### Related Works
Utilizing the non-orthogonality for large-scale multiple access [28], high-rate modulation [29], and cooperative diversity [30] techniques attracted significant attention in the fifth generation (5G) wireless network. Non-orthogonal signaling can support various wireless applications such as massive machine type communications (mMTC), ultra-reliable and low-latency communications (URLLC), and simultaneous wireless information and power transfer (SWIPT). However, there is a significant gap between NOMA and AmBC techniques, which requires sophisticated design criteria rather than a simple combination of existing RF techniques. * **Modulation and Coding Scheme (MCS)**: In AmBC, MCS is implemented by only passive RF components with limited circuit power. Advanced MCS such as an adapting power ratio in conventional power-domain NOMA, or infinite-length channel coding may not be available in low-complexity AmBC hardware. Hence, code-domain NOMA based on sparse coding is preferred to power-domain NOMA especially for AmBC applications [28; 29]. * **Channel and Detector Modeling**: Generally, AmBC modulation is operated in time domain typically using OOK [5; 6] and _M_-PSK [2]. NOMA modulation, on the other hand, is operated in frequency domain such as filtered OFDM [31] for mitigating multipath fading. Consequently, AmBC signal is severely distorted by ISI as a tag's information is conveyed in a high-rate ambient RF signal and experiences a two-way fading channel in time domain. Thus, proper channel and detector modeling are necessary in AmBC to prevent performance degradation, which may be induced by application of NOMA. Therefore, we propose non-orthogonal sparse coding and a detector to realize massive connectivity for AmBC, which bridges the significant gap between AmBC and NOMA.
# An Enhanced Lightweight IoT-based Authentication Scheme in Cloud Computing Circumstances
## 3 Proposed Scheme
### Registration Phase
#### 3.1.1 User Registration Sub-Phase  
This sub-phase is initialized by \(U_{i}\) when wants to be part of the system. The details of each step are shown in Figure 2.  
Step 1: \(U_{i}\) inserts his/her \(SC_{i}\) into a device and keys his/her \(ID_{i}\) and \(PW_{i}\). Then, \(SC_{i}\) generates a random nonce \((n_{U})\), obtains the current timestamp value \((T_{U})\) and computes:  
\[PID_{i}=h(T_{U}\parallel n_{U}) \tag{1}\]  
\[U_{i}\Rightarrow CS:M_{1}=\{ID_{i},PID_{i}\}\]  
Equation (1) is used to compute the pseudo-identity of each user.  
Step 2: After receiving the registration request message \(M_{1}\), \(CS\) verifies the validity of \(ID_{i}\). If \(ID_{i}\) is valid, \(CS\) computes:  
\[C_{1}=h(ID_{i}\parallel PID_{i}) \tag{2}\]  
\[C_{2}=h(PID_{i}\parallel h(ID_{CS}\parallel x)\parallel h(ID_{CS}\parallel y ))\oplus h(ID_{CS}\parallel x)\oplus h(ID_{CS}\parallel y) \tag{3}\]  
\[C_{3}=h(ID_{i}\parallel PID_{i}\parallel h(ID_{CS}\parallel x)\parallel h(ID_{ CS}\parallel y))\oplus PID_{i}\oplus h(x\parallel y) \tag{4}\]  
\[STORES\ C_{1}\ in\ a\ database\]  
\[CS\Rightarrow U_{i}:\ M_{2}=\{C_{2},\ C_{3}\}\]  
\(CS\) registers \(U_{i}\) by Equation (2). Equations (3) and (4) are security parameters for future authentication purpose.  
Step 3: Upon receiving the registration response message \(M_{2}\), \(SC_{i}\) computes:  
\[C_{4}=h(ID_{i}\parallel PW_{i}\parallel h(n_{U})) \tag{5}\]  
\[STORES\ PID_{i},C_{2},C_{3},C_{4},h(n_{U})\ in\ SC_{i}\]  
\(SC_{i}\) computes the local user authentication parameter using Equation (5) and stores all the security parameters received from \(CS\). The user registration sub-phase is over.  
Figure 2: User registration sub-phase.
# Visualization Program Design for Complex Piping Systems in Marine Engine Simulation Systems
## 3 Program Development and Implementation
### Implementation of Data Visualization  
In a specific ship piping network, due to the complexity of internal channels, similar to an anthill's criscrossing, these pipes cross several decks to form a three-dimensional network system. This is designed to achieve effective material transmission between devices. However, in the simulation environment, the specific length and shape of the pipes do not affect the final simulation results, so the pipe representation is more of a schematic diagram of the network layout, used to describe the flow path of the medium from inlet A to outlet B, which also has to pass through valves and pumps.  
To simplify the analysis and design of this complex network, this paper proposes to convert the complex piping network into a tabular description, recording in detail the inlets and outlets of each branch and the effective cutoff points on the branch, such as valves and pumps. Then, these textual descriptions are converted into structural diagrams, which facilitate finding all connected branches from any point in the piping network and recording the cutoff points on each branch. In this network, the changes in each cutoff point are crucial to the function and efficiency of the entire network.  
For complex piping networks with multiple pumps in parallel, pump groups in series, and series pipes with bypass branch pipes, accurately calculating the flow at any point at any time is a highly complex task. This requires not only careful consideration of all branches that allow flow, but also, taking into account that when encountering a ring-shaped piping network, the complexity will increase exponentially. Therefore, this study proposes to simplify the complex piping network to a simple piping network containing a single pump. For such a web-like structure consisting of nodes and connecting lines, the system's structural diagram becomes clearer and easier to understand.  
Most importantly, this study uses Excel spreadsheets as the carrier of information, describing the controls and piping nodes in the ship piping network. In this way, programmers only need to edit the front-end interface and Excel spreadsheet to make the program run normally. This method greatly reduces the complexity of programming and improves programming efficiency, providing a more efficient and intuitive method for the design and analysis of ship piping networks. Through this innovative method, it is possible to more effectively manage and optimize complex ship piping network systems, improving the reliability and efficiency of the system.
# Secure Image Transmission Using Multilevel Chaotic Encryption and Video Steganography
## 4 The Proposed System  
Multilevel chaotic cryptography in the proposed system refers to using multiple chaotic systems in the different stages of cryptography, including key generation, randomization, and spreading of the pixel distribution, to increase the system's level of randomness and security.  
There are five phases in the suggested system. The general structure of the hybrid system, which comprises four primary parts, appears in Figure 1:  
* _Key generation system_ The system uses a multidimensional chaotic map to create a chaotic encryption key. Because this key guarantees a great degree of randomness, the encryption procedure is impervious to brute-force attacks.
* _Image encryption-decryption_ The system improves security by encrypting the input image using the AES technique with the created chaotic key. Encryption stops unwanted access by making the image data unrecognizable. Decryption reverses the encryption at the recipient's end using the same chaotic-AES method.
* _Video segmentation_ It separates the video into frames and chooses the frames that will include the encrypted image blocks with a selection technique. This step optimizes the balance between security and imperceptibility.
* _Steganography_ The system uses Least Significant Bit (LSB) steganography to embed encrypted image blocks into some video frames. This method preserves the integrity of the video content while guaranteeing that the embedded data is not visually noticeable.
* _Extracting Hidden Images from Video_ The technology extracts the steganographic frames with the secret image at the receiver's end. It safely restores the original image by reconstructing and decrypting the removed blocks.  
AES encryption, chaotic key generation, and steganographic embedding work together to improve system security and provide a strong defense against various threats.  
Each component includes a set of substeps, as explained in the following subsections.  
System 1: This system consists of five chaotic maps (Arnold, piecewise, Ikeda, ginger-bread, and standard) that are responsible for generating the first key. System 2: This system consists of two chaotic equations (Henon map, Zaslavsky map) to maximize randomness and generate the second key. Chaotic controller: Contains two chaotic tent map equations that select the first generated encryption key or the second generated encryption key based on a particular condition. Generated key: The randomness of the generated key is evaluated by applying the NIST test. AES algorithm module: The encryption key generated from multilevel chaotic equations is combined to encrypt secret images. Steganography module: The video is divided into frames, and the encrypted secret image is hidden in the frames using the LSB technique. The overall process of the proposed method is illustrated in Algorithm 1.  
Figure 1: A hybrid framework for the proposed system.