esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Analysis of Port Competition Mode and Equilibrium Result
With the increase in \(C_{B}^{sea}-C_{A}^{sea}\), the maritime transportation cost advantage of port A is much greater than the land transportation cost of port B. Therefore, more shippers select port A for cargo transportation with the increase in \(C_{B}^{sea}-C_{A}^{sea}\); the equilibrium demand of port A increases, and the equilibrium price and profit of port A keep increasing. If port A has an advantage in maritime transportation cost and port cost, an increase in cross-border transportation costs of port B will weaken its competitiveness, while the competitiveness and profit of port A will increase. However, if port A has no advantage in both maritime transportation cost and port cost, within a certain range, the profit of port A decreases with the increase in cross-border transportation costs of port B. Only when the cross-border transportation cost of port B is sufficiently high, its disadvantage in port and sea transportation cost can be offset, resulting in an increase in the profit of port A. It can be seen in Equation (19) that \(\pi_{A}^{*}\) is a quadratic function with respect to \(C_{bB}^{land}\). When \(C_{B}^{sea}-C_{A}^{sea}+(2+b)\sum\limits_{m=1}^{M}w_{m}\left(\delta^{m}+ \varepsilon\frac{1}{\overline{V}^{m}}\right)+2H_{B}+H_{A}+C_{B}^{port}-C_{A}^{ port}>0\), \(\pi_{A}^{*}\) increases with \(C_{bB}^{land}\). When \(C_{B}^{sea}-C_{A}^{sea}+(2+b)\sum\limits_{m=1}^{M}w_{m}\left(\delta^{m}+ \varepsilon\frac{1}{\overline{V}^{m}}\right)+2H_{\(C_{A}^{port}\ <\ 0\), if \(C_{ik}^{land}\ \in\ \left[0,\ C_{A}^{sea}-C_{B}^{sea}-(2+b)\sum\limits_{m=1}^{M}w_{m} \left(\vec{e}^{m}+\epsilon\frac{1}{1+m}\right)-2H_{B}-H_{A}-C_{B}^{port}+C_{A}^{ part}\right]\), \(\pi_{A}^{*}\) decreases as \(C_{kl}^{land}\) increases, and if \(C_{A}^{land}\ \in\ \left[\ C_{A}^{out}-C_{B}^{sea}-(2+b)\sum\limits_{m=1}^{M}w_{m} \left(\vec{e}^{m}+\epsilon\frac{1}{1+m}\right)-2H_{B}-H_{A}-C_{B}^{port}+C_{A}^{ part},+\infty\right]\), \(\pi_{A}^{*}\) increases as \(C_{kl}^{land}\) increases. \(\square\)  
This indicates that when port A has advantages in both port cost and maritime transportation cost over port B, meaning the port cost and maritime transportation cost of port A are lower than port B, an increase in cross-border transportation costs to port B will result in higher land transportation costs for port B. Consequently, shippers tend to choose port A, leading to higher demand for port A, stronger competitiveness for port A, and higher profits. However, when port A does not have any advantage in port cost and maritime transportation cost compared to port B, even if the cross-border transportation cost to port B increases, it cannot offset the disadvantage of port A in terms of port cost and maritime transportation cost. Only when the cross-border transportation costs of port B reach a certain level can the land transportation costs of port A become more significant, thus offsetting the disadvantage of port A in port costs and maritime transportation costs, resulting in an increase in the profit of port A with an increase in cross-border transportation costs.
###### Abstract  
The growth of frequency-usage devices has made the electromagnetic spectrum posture complex, resulting in an urgent demand for frequency-usage posture cognition. However, the sensing of space-based platforms is limited by the transmission capacity of the satellite-to-ground link and the satellite processing capacity, which makes on-satellite data analysis and posture generation lack the efficient means. Facing the above issues, an idea of a knowledge graph construction and semantic representation for low Earth orbit (LEO) satellite spectrum sensing data is designed in this paper. In the designed construction process, technologies such as knowledge extraction, ontology construction, knowledge fusion and knowledge visualization are utilized to efficiently analyze on-satellite sensing data. Moreover, the constructed spectrum knowledge graph can be applied in the analysis and prediction of frequency-usage behavior and intelligent spectrum management, which exhibits the effectiveness of the spectrum knowledge graph. Finally, the further development of the spectrum knowledge graph is foreseen.  
LEO spectrum sensing; knowledge graph; ontology construction; semantic extraction Article Research on Knowledge Representation and Semantic Representation of Low Earth Orbit Satellite Spectrum Sensing Data.  
[PERSON], [PERSON], [PERSON], [PERSON], [PERSON], G. Research on Knowledge Graph Construction and Semantic Representation of Low Earth Orbit Satellite Spectrum Sensing Data.
# Digital Health Technology for Stroke Rehabilitation in Canada: A Scoping Review
## 3 Results
### Gaming Systems  
Interactive rehabilitation tools, including gaming-based systems, have been reported to enhance fine motor function, engagement, and self-confidence [27; 28; 32; 35]. Commercial gaming platforms, such as Wii-based rehabilitation, have demonstrated potential benefits in improving motor skills and increasing confidence in performing daily activities [35]. However, accessibility and clinician involvement remain key barriers to adoption [28].
# Adversarial Machine Learning for NextG Covert Communications Using Multiple Antennas
## 4 Adversarial Perturbations Using Multiple Antennas at the CJ
### Inversely Proportional to Channel Gain (IPCG) Attack  
In contrast to the PCG attack, the CJ allocates more power to weak channels to compensate for the loss over the weak channels, i.e., inversely proportional to the channel gain. The perturbations that are transmitted by each antenna are generated using the MRPP attack and the power for each antenna is determined to be inversely proportional to the channel gain. The algorithm is the same as Algorithm 2 except that \(w_{i}\) changes to be inversely proportional to the channel, i.e., \(w_{i}=\frac{\mathbbm{1}}{\|\mathbf{h}_{c;i}\|_{2}}\frac{1}{\sum_{j=1}^{d}\| \mathbf{h}_{c;i}\|_{2}},i=1,\cdots,q\).
# Quantum Key Distribution with Post-Processing Driven by Physical Unclonable Functions
## 3 Conclusions
If one is willing to accept a computationally secure system, PUFs can be combined with standard public key cryptosystems in order to generate and distribute keys between users. In particular, the key that is generated from a PUF device may serve as a private key, or it can be used as a random seed for the generation of a private key. Subsequently, building upon the private key, the corresponding public key is generated, which becomes publicly available through a trusted public key server. An advantage of such an asymmetric cryptosystem is that it allows for the implementation of various cryptographic tasks beyond the generation and the distribution of a key, including digital signatures. At the same time, the pair of private-public keys is bound to the PUF device. Throughout this work, we have adopted a rather general theoretical framework, which is not restricted to a particular type of PUF. The present results pave the way for the integration of PUFs in currently used QKD systems, but there are many practical issues that deserve further investigation in order to identify which type of PUF better serves the needs of QKD networks. To this end, one has to take into account various facts including the required key lengths, the size of the network, the robustness of the PUF in the presence of environmental fluctuations, etc. Optical PUFs may be a very promising candidate because they are considered to be among the strong PUFs, and they can typically support long keys (thousand of bits) [25, 35, 42]. Moreover, they are compatible with QKD infrastructure and, in principle, they are amenable to remote quantum readout [46]. Remote quantum readout of optical PUFs is very attractive if one is interested in saving classical resources, at the cost of introducing limitations in the spatial separation between the users and the KDC. However, all the known quantum readout schemes [47, 48, 49] are currently limited to very short distances (of the order of 1 km), and there is a need for their extension to distances comparable to the ones that can be covered by standard QKD systems. Only experimental research may shed light on the integration of PUFs in operational QKD networks and provide answers to many of these questions. Conceptualization, G.M.N. ; methodology, G.M.N. and M.F. ; formal analysis, G.M.N. and M.F. ; writing--original draft preparation, G.M.N. ; writing--review and editing, G.M.N. and M.F. All authors have read and agreed to the published version of the manuscript. This research was co-funded by the European Union under the Digital Europe Program grant agreement number 101091504. Moreover, it has been funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)--SFB 1119--236615297. Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Data is contained within the article. The authors are grateful to [PERSON] for useful discussions.
## 2 Data and Methodology  
### Description of the Maritime Target Dataset  
A new dataset has been established that consists of typical targets in the river and sea regions well suited for the study and application of object recognition in marine engineering problems. The data came from the following sources: photographs taken at the harbors, pictures taken by the unmanned surface vehicle, and images collected from the websites. After the collection of the dataset, the images were annotated manually in the YOLO format. The dataset contains a total of more than seven thousand real images composed of ten classes of maritime objects, including ships (passenger ships, sailboats, cargo ships, etc.) and devices and structures (rail bars, lighthouses, docks, etc.), with an approximate ratio of 7:1:2 for the training, validation, and test sets. Figure 1 shows the distribution of targets from each of the ten categories in this dataset for training and validation, and image samples are displayed in Figure 2. Input images of the dataset vary in resolution and size. Images with medium to large targets accounting for the majority of the data are considered as one of the features of this dataset.  
Challenges of this dataset come from the following aspects. Firstly, target classes are unevenly distributed, with certain types accounting for very small percentages among all the categories. In addition, the dataset contains a small portion of what can be referred to as hard examples, which include objects that appear small or tiny and images blurred due to harsh weather conditions. Moreover, new categories such as dock and rail bar are incorporated in the data, and in particular, docks have rather different characteristics compared to common categories such as boats or ships. These factors can potentially bring barriers to the learning of the model, which makes it necessary to put forward well-designed or specialized algorithms for the recognition of maritime objects.
## 2 Background
### IoT Challenges
#### 2.3.3 IoT Security  
With the steady increase over the last decade in IoT devices, IoT security has become imperative, and security can be categorized as the largest challenge of the IoT. The major security challenges are as follows:  
1. Confidentiality: Making the data secure ensures that only authorized individuals have access, thus preventing access by unauthorized personnel [32].
2. Heterogeneity: Many companies around the world are actively working on the IoT, producing products and devices. Due to non-standardization, different protocols and operating systems are being developed, and the configuration of these devices is also different. Thus, there is a need for uniformity and homogeneity [32].
3. Integrity: Data integrity involves accuracy and completeness. When the data are transferred between devices based on a wired or wireless network, messages may be garbled during wireless IoT transmission owing to attenuation, distortion, or noise [32].
4. Availability: Availability is one of the main factors in the elevation and improvement of the IoT based on the hardware or network; however, the IoT is still vulnerable to massive cyberattacks [32].
# Improvements in Rock Mass Description for Stope Design by Geophysical and Geochemical Methods
## 1 Introduction  
Selective mining of ore in underground environments is achieved by blasting, which creates open spaces known as stopes. Rock joints and other discontinuities in the rock mass can cause instability and collapses in stope walls and roofs, leading to ore dilution and safety concerns. Stope design, therefore, is a critical component of underground mining that aims to optimize ore recovery, minimize ore dilution and production costs, and maximize profits while ensuring safety. Key design parameters in stope design include ore geometry, rock mechanics conditions, mine infrastructure, and available equipment. Large stopes lower the unit costs but may lead to unstable stopes. Successful stope design requires a sound understanding of ore geology and rock mass conditions [1]. Real-time acquisition of mineralogical data of the ore improves grade control and helps to optimize ore processing.  
Current methods in stope design, although effective to an extent, often fall short in real-time, accurate characterization of the ore body and the surrounding rock mass. This gap leads to reactive rather than proactive decision-making, where changes in stope design are often made post factum, resulting in increased costs and safety risks.  
This research aims to improve the stope design process by integrating advanced geophysical and geochemical methods, thereby offering a proactive approach to mining planning. The specific objectives of this study are not only aimed at specifying mineralogy and estimating ore content but also at mapping the structural features of the rock mass, including its position, direction, and continuity. The novelty of this study lies in its comprehensive, real-time acquisition of mineralogical data at the tunnel face using laser-spectral measurements. This approach can offer immediate, on-site analysis of oregrade and mineral composition, thereby facilitating more accurate and efficient ore recovery. In addition, understanding rock mass conditions using innovative, non-destructive geophysical methods, coupled with laboratory analyses and photogrammetric rock mass characterization, is investigated. This work represents a significant departure from conventional stop design methodologies, marking a substantial advancement in the field. The study began with an extensive literature review to identify current challenges in stope design and to pinpoint areas where existing practices fall short. This was complemented by a survey directed towards mining professionals, ensuring that the research addresses practical, industry-specific challenges.  
This multifaceted approach, encompassing both theoretical and practical aspects, aims to develop a data-driven methodology for stope design. The integration of detailed mineralogical information with rock mass characteristics is set to provide a more robust and accurate framework for stope design, addressing the critical challenge of maintaining stope stability while optimizing ore recovery.
###### Abstract  
Distinguishing composite remnants from tooth structure after trauma splint removal can be challenging. This study aimed to compare the Fluorescence-aided Identification Technique (FIT) with conventional light illumination (CONV) in terms of accuracy and time required for the detection of composite remnants after trauma splint removal. Ten bovine tooth models containing anterior teeth from 12 to 22 with composite remnants after trauma splint removal were used. These models were examined by 10 students and 10 general dentists. Each examiner assessed the 10 models using CONV or FIT three times with an interval of 2 weeks each using a prototype fluorescence-inducing headlamp with a spectral bandwidth of (405 \(\pm\) 7) nm for FIT and a dental unit lamp for CONV. The examiners charted the location of identified composite remnants, and the procedure time needed for each method was recorded. Statistical analysis was performed with R 3.2.2 software with a significance level of \(\alpha\) = 5%. FIT was more accurate and less time-consuming than CONV (\(p<\) 0.001). There were no significant differences between dentists and students concerning accuracy (CONV: \(p\) = 0.26; FIT: \(p\) = 0.73). Students performed FIT significantly faster than the dentists (\(p<\) 0.001). FIT is a quick and reliable method of identifying composite remnants after trauma splint removal.  
Keywords:composite detection; fluorescence-aided identification technique; titanium trauma splint (TTS) removal +
Footnote †: journal: Applied Sciences
# Enhanced Conjunction Assessment in LEO: A Hybrid Monte Carlo and Spline-Based Method Using TLE Data
## 3 Physical Characterization and Results
### Case Study Results and Relative Motion Analysis
\begin{table}
\begin{tabular}{c c c c c c c} \hline \multirow{2}{*}{**Algorithm**} & \multirow{2}{*}{**Time of Epoch**} & \multirow{2}{*}{**TCA**} & \multicolumn{2}{c}{**TCA Deviation**} & \multirow{2}{*}{**Min Distance**} & \multirow{2}{*}{**Min Distance**} & \multirow{2}{*}{**D**} \\  & & & & **(s)** & & **km** & **Reference (km)** & \\ \hline Comparison data & & 2025-04-25 & & & 0.176 & & 29798 \\  & 2025-04-25 & & 18:56:38.532 & & & 0.026 & \& 60876 \\ \hline Multi-stage & 15:18:46.0 & 2025-04-25 & & & & & \\  & 18:56:38.501 & & & & & & \\ \hline Comparison data & & 2025-05-15 & & & & & \\  & 2025-05-14 & & 22:37:34.909 & & & & \\ \hline Multi-stage & 17:06:12.0 & 2025-05-15 & & & & & \\  & 22:37:34.912 & & & & & \\ \hline \end{tabular}
\end{table} 
Table 2: Error assessment of time of closest approach (TCA) and miss distance compared to reference data.
## 1 Introduction
The typical frequency range of LIPUS is between 40 kHz and 5 MHz with intensity levels between 5 and 1000 mW/cm\({}^{2}\) and the commonly burst excitation used is characterized by a pulse width of 200 us and pulse repetition frequency (PRF) of 1 kHz, corresponding to a duty cycle of 20%. LIPUS is used for stimulating healing in different tissues for a variety of applications, especially in rehabilitation medicine, bone-fracture healing, soft-tissue regeneration, and inflammatory responses inhibition. At a cellular level, LIPUS has also been observed to increase migration and proliferation of aortic endothelial cells, proliferation of fibroblasts, Schwann cells, and other cell types [5]. While the effect of HIFU is associated with generated heat, the therapeutic effects of LIPUS are traced back to low intensities within the range of 0.07-3 W/cm\({}^{2}\) Spatial Average Temporal Average (SATA) [6] and frequencies of 0.5-5 MHz and a treatment duration of 5-20 min per day [7]. Many studies showed evidence that LIPUS could regulate cell proliferation and differentiation [8]. Induced biomechanical effects, such as radiation force, acoustic streaming, and strain gradients, seem to play a major role in triggering cellular responses at LIPUS exposures. In order to provide good understanding on the effects of magnetic fields and US on cancer cells and tissues, further studies are required to establish their efficiency in clinical environments. For example, comparison of results in different literature appears to be very difficult due to large variations in US treatment conditions [9]. Pancreatic Ductal Adeno Carcinoma (PDAC) is one of the most common causes of cancer-related death with a 1-year survival rate lower than 20% and a 5-year survival rate of 8%, regardless of the stage. The disease is almost always fatal, and its incidence is forecasted to continuously grow in the next years, unlike other cancer types, whose incidence is declining. For these reasons, PDAC represents an urgent medical need, and the accomplishment of new treatments is therefore mandatory. The aim of this study is the research and optimization of the parameters for the ultrasound treatment of pancreatic cancer cell lines, PANC-1, Mia PaCa-2 and BxPc3, in order to induce a resonance effect in cell capable of damaging them and eventually leading to cell death [10].
## 4 Discussion: Optical vs. Electromagnetic Methods
The optical methods offer more detailed results by registering micrometric coating features; however, ready-to-use (i.e., not requiring mathematical corrections), fast, and in situ measurements can be performed with ECs. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Sample**} & **OCT (\(\mu\)m)** & **OCT Mean** & \multirow{2}{*}{**Std. dev. (\(\mu\)m)**} & **CRM = (\(\mu\)m)** & **CRM = Mean** & \multirow{2}{*}{**Std. dev. (\(\mu\)m)**} & **Eddy Current** & \multirow{2}{*}{**Std. dev. (\(\mu\)m)**} \\  & **Min./Max.** & & & & & & & \\ \hline PB-72\({}_{\text{Na}}\) & 21.3/60.3 & 36.7 & 12.7 & 57.9/67.4 & 62.3 & 4.8 & 43 & 2 \\ PB-72\({}_{\text{Na}}\) & 17.7/50.1 & 28.4 & 9.3 & 28.3/86.6 & 36.1 & 0.8 & 32 & 2 \\ PB-72\({}_{\text{Na}}\) & 8.9/32.8 & 15.2 & 5.6 & 6.7/97.9 & 8.2 & 1.5 & 12 & 1 \\ \hline PB-44\({}_{\text{Na}}\) & 17.7/50.0 & 28.7 & 10.0 & 25.8/29.2 & 27.7 & 1.7 & 30 & 1 \\ PB-44\({}_{\text{Na}}\) & 7.7/25.3 & 15.3 & 4.2 & 10.8/14.9 & 12.3 & 2.3 & 10 & 1 \\ PB-44\({}_{\text{Na}}\) & 6.6/11.1 & 8.0 & 1.4 & 7.2/9.5 & 8.2 & 1.1 & 6 & 1 \\ \hline Zaprova & 98/28.4 & 18.8 & 5.0 & 27.5/29.0 & 28.1 & 0.8 & 20 & 1 \\ Zaprova & 7.4/21.2 & 13.4 & 3.4 & 9.0/10.2 & 9.5 & 0.6 & 10 & 1 \\ Zaprova & 6.5/10.6 & 7.3 & 1.1 & 5.1/5.8 & 5.5 & 0.3 & 4 & 1 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparison of thickness measurements obtained with the three techniques: OCT, CRM, and EC. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Technique**} & **Portable** & **Area Investigated 1** & **Data Correction** & **Contactless** & **Measure Time** &
\begin{tabular}{c} **Corrosion** \\ **Interference** \\ \end{tabular} \\ \hline OCT & Yes & Smallest area: 13 \(\mu\)m\({}^{2}\) & Yes & Yes & Relatively fast & No \\ CRM & No & Smallest area: \(\sim\)1.77 \(\mu\)m\({}^{2}\) & Yes & Yes & Slow & No \\ EC & Yes & 19.63 mm\({}^{2}\) (\(\diameter\)5 mm) & No & No & Fast & Yes \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Main features of each technique employed in this work.
# From Analogue to Digital Photogrammetry: Documentation of Padise Abbey in Two Different Time Stages
###### Abstract  
Exploration of historical buildings during their life cycles is one of many aspects of the cultural heritage research. For studying different conditions of historical buildings over time, it is convenient to use photogrammetric surveys carried out in different time stages. Modern photogrammetric methods give the possibility to use archived analogue photogrammetric data, re-process them, and achieve new potentially valuable results with sufficient geometric accuracy and with high visual quality. The paper presents re-processing of analogue archival photogrammetric images captured by a metric camera in 1991 and compares the results to the new photogrammetric survey with a digital camera. The object of interest is Padise Abbey in Estonia. In 1991, parts of the abbey were in poor condition and conservation and renovation works were at an early stage. Nowadays, the abbey is partly renovated, and the results of the new photogrammetric survey give an opportunity to study two completely different conditions.  
photogrammetry; structure from motion; analogue images; UMK metric camera; Padise Abbey +
Footnote †: journal: Applied Sciences