esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
The main contributions of this study lie in addressing the gaps in sports analytics by advancing beyond mere object recognition to encompass tracking and the extraction of key events for interpreting and generating commentary for sports matches. While previous YOLO-based models have significantly improved the accuracy of ball and human detection, they have not been applied to analyze matches or generate broadcast commentary. This study proposes a method to optimize sports commentary generation by fine-tuning existing models, demonstrating the feasibility of achieving high-quality results. Additionally, recognizing the unique challenges in the sports domain--such as uncontrolled environments, complex backgrounds, inconsistent lighting, and fast-moving players--this study incorporates domain knowledge specific to basketball to distinguish between teams, players, and referees, while also recognizing in-bounds and out-of-bounds events. By implementing an algorithm tailored to these challenges, including the detection of blurry ball pixels and the differentiation of participants, this study effectively bridges the gap between object recognition and comprehensive sports game analysis, enabling robust commentary generation. Finally, through this study, it is expected that by recognizing players' actions and play information from video input alone and automatically generating sports broadcasts, the method can be applied to less popular sports that are not currently broadcast.
# Machine Learning-Assisted Adaptive Modulation for Optimized Drone-User Communication in B5G
## 1 Introduction
### Motivation and Contributions  
The key idea of adaptive modulation is to achieve a particular Bit Error rate (BER) threshold by reducing the energy per bit per noise ratio. However, this adversely affects spectral efficiency, and hence, a choice of the modulation scheme for different channel conditions has to be made. The contributions of this paper are:  
1. We build a system model in which we consider switching between various phase shift schemes such as binary Phase-Shift Keying (BPSK), Quadrature Phase-Shift Keying (QPSK), 16-Quadrature Amplitude Modulation (QAM), and 256-QAM modulation schemes in order to satisfy the required BER threshold.
2. We analyze the performance of the drone-user communication with various rain, LoS conditions.
3. We propose an algorithm based on ML to intelligently adapt to the modulation scheme that offers the best data rate without sacrificing error performance due to atmospheric disturbances.
## 4 Results and Discussion
For the ratio (\(L_{0}\)/\(H_{1}\))\({}_{0}\) = 0.05, an injection time of \(t_{\rm mmm}\) = 27.9 s is obtained, and the ratio \(L_{0}\)/\(H_{0}\) = 0.2 leads to a once minimized injection time of \(t_{\rm m}\) = 87.9 s, which is, about of 215.0% higher than the previously obtained optimal geometry. It is then possible to significantly improve the performance of the studied system even in the last level of optimization. In a general sense, the results demonstrate that for the T-shaped channel, all geometrical ratios (degrees of freedom) affect the filling time of resin impregnation in a porous domain. They also show that one degree of freedom has a strong influence over the optimal ratios of other geometric ratios, e.g., the ratio \(H_{0}\)/\(H_{1}\) affected the optimal ratios of (\(L_{1}\)/\(H_{1}\))\({}_{00}\) and (\(L_{0}\)/\(H_{0}\))\({}_{0}\). All the geometrical parameters studied here (\(L_{1}\)/\(H_{1}\), \(L_{0}\)/\(H_{0}\), and \(H_{0}\)/\(H_{1}\)) has some sensibility in the infusion process and cannot be neglected. Moreover, a comparison between the performance of the T-shaped and I-shaped empty channels, for the same conditions, demonstrates that the thrice-optimized T-shaped channel leads to performance that is almost three times superior to that achieved by the optimal I-shaped configuration. In the present fluid dynamic conditions, where resin flow has little advective dominance, the rectangular porous plate can be viewed as an elementary construction of multiple structures generated by the replication of a porous plate in \(x\)- or \(y\)-axes. In this case, multiple optimal configurations of I and T-shaped channels can be associated in a series and/or parallel using the optimal configurations reached in this work.
## 4 Fidelity of the Front-End  
To further quantify the fidelity of the front-end system, long-term energy stability is monitored continuously and is usually below 2% rms after XPW. Figure 5(a) is an illustration of typical energy fluctuations over a few minutes of the pump laser, amplified and filtered pulses.  
**Figure 5. (a)** Simultaneous measurements of energy fluctuations of the pump laser, amplified and filtered pulses over 16 min. Over one hour, typical rms energy deviations of the pump, amplifier and XPW pulses are 0.3%, 1% and 1.6% respectively; (b) Relative CEP drift with feedback control on the oscillator of the amplifier (measured after the XPW setup with no BaF\({}_{2}\) crystal) and XPW pulses. Energy and CEP stability measurements have been done on the same day under similar experimental conditions.  
CEP stability of the front-end system is the last critical feature to be characterized. To estimate it, a few microjoules of the XPW pulse are split off, compressed with chirped mirrors and sent into a collinear f-to-2f interferometer (APS 800, Menlo Systems). The slow CEP drift of the output pulses at 1 kHz is pre-compensated by a feedback loop to the oscillator locking electronics. For the measurement, the spectrometer acquisition time is 1 ms and the cycle loop time of the APS software is 100 ms. Results are shown in Figure 5(b). The rms phase error is 170 mrad over 16 min. Although slightly higher than the amplifier (typically 100 mrad rms), this value confirms the robustness of the XPW filter. We estimate the degradation of the CEP stability to be partly due to the measurement itself, which is affected both by the input pulse-to-pulse stability and by the limited ability of the APS device to handle such short (spectrally broad) pulses.
# Leveraging Large Language Models for Enhancing Safety in Maritime Operations
## 3 Understanding Large Language Models
### Limitations and Considerations  
Despite their considerable promise, LLMs present several limitations and considerations that must be addressed when contemplating their integration into maritime safety operations. One significant challenge is the substantial computational resources required for training [105] and deploying these models. The training process demands high-performance computing infrastructure and considerable energy consumption, which may not be feasible for all organizations.  
Data requirements also pose a challenge. While LLMs are trained on large, diverse datasets, the quality and representativeness of the data are critical. If the training data contain biases or inaccuracies or are unrepresentative of the maritime context, the model's outputs may be flawed or misleading. This is particularly concerning in safety-critical applications where erroneous information can have severe consequences.  
Another limitation is the potential for LLMs to generate outputs that are contextually plausible but factually incorrect. This phenomenon, sometimes referred to as \"hallucination,\" can occur because the models generate text based on learned patterns rather than verified knowledge bases. In the context of maritime safety, reliance on inaccurate information could compromise decision-making processes [106; 107].  
Moreover, LLMs lack true understanding and consciousness; they do not possess awareness or intent. They may fail to recognize ambiguities or nuances that a human expert would perceive, and they cannot replace human judgment, especially in complex or unforeseen situations.  
Ethical and legal considerations also arise, particularly concerning accountability. The use of LLMs in decision-making processes raises questions about responsibility in the event of errors or accidents. Regulatory frameworks governing the use of AI in maritime operations are still evolving, and operators must navigate these uncertainties carefully [108; 109].  
Finally, the integration of LLMs into existing systems requires careful planning to ensure interoperability and cybersecurity. Protecting sensitive data from breaches and ensuring that AI systems do not introduce new vulnerabilities are essential considerations [110].  
While LLMs offer transformative potential for enhancing maritime safety, their limitations necessitate a cautious and informed approach to their adoption. Balancing the benefits with the associated risks and challenges is critical to leveraging these technologies effectively and responsibly within the maritime industry.  
With a foundational understanding of LLMs established, the next section explores their practical applications in maritime operations, highlighting real-world use cases and benefits.
# Operational Modal Analysis and Safety Assessment of a Historical Masonry Bell Tower
## 2 The Case Study: The Bell Tower of the St. Lucia Church in Cellole (CE)  
### Geometrical Survey  
The structure under investigation (Figure 1) is the bell tower of the Church of St. Lucia in Cellole (Caserta Province, Italy). The tower is adjacent to the homonymous church, with which shares the ground floor rooms.  
A complete laser-scanner 3d survey of the church and the tower was performed in order to define the main geometrical characteristics. The instrument was Leica BLK360 Imaging Laser Scanner (Wetzlar, Germany), while the raw data were then processed by Cyclone Registrer 360 software. The whole complex including the church and the bell tower was shot from 60 points. In Figure 2 the global view of the 3d laser scanner survey is shown.  
The tower has a rectangular base and can be geometrically divided into five sectors. The first sector extends vertically to approximately 5.30 m, with external dimensions of 4.75 \(\times\) 3.80 m. The second and third sectors have the same external dimensions as the first one, but with slightly chamfered corners on the southern side. Both sectors have a vertical extension of about 3.50 m, while the fourth sector (constituting the belfry of the tower) is 2.80 m high, with a smaller in-plane dimension of 3 m. The final sector is a reduced extension of the tower, approximately 2.40 m high, probably added at a later time, and also presents an external bell.  
In plan, the tower can be divided into two parts along its major dimension throughout its height. Specifically, it features a transversal wall that defines two sections: a cave-like section on the southern side and a complex system of flying buttresses that support an internal staircase, allowing access from the ground level to the top sector.  
The complete geometrical survey of the tower, including the plan views at the different sectors and two sections, is provided in Figure 3.  
Figure 1: The tower of the St. Lucia Church in Cellole (CE): (**a**) south-west, (**b**) south and (**c**) north views.  
Figure 2: Global view of the 3D laser scanner survey.  
Figure 3: Geometrical survey of the tower of St. Lucia Church in Cellole (CE).
# Effect of Ionic Liquids on the Isobaric Vapor-Liquid Equilibrium Behavior of Acetone-Chloroform
###### Abstract  
Isobaric vapor-liquid equilibrium (VLE) data of the ternary system acetone + chloroform + 1,3-dimethylimidazolium dimethylphosphate ([MMIM][DMP]) or 1-ethyl-3-methylimidazolium diethylphosphate ([EMIM][DEP]) were obtained at 101.3 kPa. Results indicated that the addition of [MMIM][DMP] or [EMIM][DEP] could eliminate the azeotropic point of the binary system of acetone + chloroform when the mole fraction of ionic liquids (ILs) was above 0.15. Besides, the experimental data could be well correlated by the nonrandom two-liquid (NRTL) model. The structures as well as interactions between molecular solvents (acetone, chloroform) and the ion pairs ([MMIM][DMP], [EMIM][DEP]) were studied by quantum chemical calculations. The result indicated that the interaction energies (\(\Delta E\)) follow the order of \(\Delta E\)(acetone + [EMIM][DEP]) \(>\Delta E\)(acetone + [MMIM][DMP]) \(>\Delta E\)(chloroform + [EMIM][DEP]) \(\approx\Delta E\)(chloroform + [MMIM][DMP]), and chloroform had stronger affinity to ionic liquids than acetone.  
ionic liquid; vapor-liquid equilibrium; NRTL model; acetone; chloroform; quantum chemical calculation
# Efficient Conjunctive Keywords Search over Encrypted E-Mail Data in Public Key Setting
## 5 Performance Evaluation
### Experimental Results
#### 5.2.3 Comments  
Based on the theoretical analysis and experimental results, we find that our scheme is better than ZZ11 except the time cost of key generation and the storage cost of \(sk\). Note that the key generation algorithm does not run often and \(sk\) is stored only several copies. So, we can argue that our scheme has a better performance than ZZ11. Compared with OT15, our scheme is better than it except the space cost of trapdoor. Considering that \(n\) is not very large, we can argue that our scheme is much practical than OT15. Compared with ZLW19, our scheme is better than this scheme except the time cost of trapdoor generation and the storage cost of trapdoor. The reason is that the time and space cost of trapdoor are both linear with \(m\), not \(n\). However, since \(n\) and \(m\) are commonly small, we can argue that our scheme is still much more practical than ZLW19.  
For our scheme, when \(n=10\), the average time costs of index building and testing of one document are 63 ms and 62 ms, respectively. The average time costs of key and trapdoor generation are 10 ms and 119 ms, respectively. Thus, we can argue that our scheme is very practical in the mobile setting in which data receiver has limited computation capacity. Note that the index structure for our scheme is that each document has its own index. We can accelerate the process of the index building and testing by using the parallel computation mechanism. What is more, our scheme can efficiently support dynamic operation, that is, documents deletion and insertion, on the account of the property of the index structure. According to these analysis, we can argue that our scheme is very suitable for the actual e-mail system.
# Enhancement of PV Panel Power Production by Passive Cooling Using Heat Sinks with Perforated Fins
## 3 Materials and Methods  
### Problem Description  
The goal of this work was to develop a numerical model regarding the passive cooling of the PV panels, through perforated and non-perforated heat sinks, and determine the enhancement of operating temperatures compared to the base case (without cooling). A photovoltaic panel with an area of approximately \(S\) = 1.6 m\({}^{2}\) was studied in a fixed position and tilted at 45\({}^{\circ}\) from horizontal, as well as in variable solar radiation, wind velocity and ambient temperature. This setup, together with the wind direction towards the backside of the PV panel, was established according to NOCT conditions [14] in order to validate the model.  
A common monocrystalline Si-based PV panel (AE Solar AE320 HM6-60), with an advantageous position of the junction box, was analyzed with the following technical data (Table 1) [43].  
\begin{table}
\begin{tabular}{c c} \hline \hline \multicolumn{3}{c}{**AE Solar AE320 HM6-60 PV Panel**} \\ \hline \(P_{mp}\) & 320 Wp \\ \(V_{mp}\) & 33.40 V \\ \(I_{mp}\) & 9.59 A \\ \(V_{cc}\) & 40.90 V \\ \(I_{sc}\) & 10.15 A \\ \(\eta\) & 19.30\% \\ \(\beta\) & \(-\)0.37\%/\({}^{\circ}\)C \\ \(t_{NOCT}\) & 47 \({}^{\circ}\)C \\ Dimensions (\(L\times l\times h\)) & 1665 mm \(\times\) 996 mm \(\times\) 35 mm \\ \hline \hline \end{tabular}
\end{table}
Table 1: General characteristic for the considered PV panel.  
A step-by-step analysis of heat sink usage for cooling PV panels was conducted. After the initial validation of the base case--PV panel without heat sink--a total of six photovoltaic panels with attached heat sinks were analyzed. Two of them were non-perforated, while the other four had perforated fins.  
The heat sink consisted of a metal plate with copper attached to the photovoltaic panel and perforated or non-perforated metal fins, Figure 1. The role of the designed holes on the fins was assumed to be both quantitative (by reducing the amount of material necessary for device construction) and qualitative (by amplifying the turbulence and heat transfer in the immediate vicinity of the PV panel).  
Due to preliminary analysis and the literature review [11; 32; 34; 41], the 30 mm and 60 mm diameter circular perforations distributed on a single row turned out to be feasible. It emerged that other shapes, dimensions or multiple rows of perforations were heading towards lower performance of the heat sink (the operating temperatures were at least 2-3 \({}^{\circ}\)C higher). It must be specified that the literature comprises a diversity of heat sinks with different approaches of fins [42; 44]. The present study is focused on using heat sinks with continuous fins.  
Two types of heat sinks were analyzed:  
Type 1--heat sinks with horizontal (transversal) fins of 100 mm height (with 3 subtypes: non-perforated, \(\Phi\) = 30 mm perforations, \(\Phi\) = 60 mm perforations);  
Type 2--heat sinks with vertical (longitudinal) fins of 100 mm height (with 3 subtypes: non-perforated, \(\Phi\) = 30 mm perforations, \(\Phi\) = 60 mm perforations).
## Basic Theory
### Fruit Fly Optimization Algorithm  
Fruit fly Optimization Algorithm (FOA), similar to other biomimetic interactive evolutionary computation algorithm, simulates the foraging process of fruit fly. The procedure of basic FOA can be summarized as follows and the schematic diagram is showed in Figure 2.  
Step 1.1: Initialize the parameters: population size \(PS\), maximum iteration number \(IN_{max}\), location range \(LR\) and the fly distance range \(FR\).  
The initial position of the fruit fly group is represented as follows:  
\[\left\{\begin{array}{l}X\_axis=rand(LR)\\ Y\_axis=rand(LR)\end{array}\right., \tag{12}\]Step 1.2: An individual fruit fly uses its olfactory sensation to find food, the random searching direction and distance is given as follows:  
\[\left\{\begin{array}{l}X_{i}=X\_axis+rand(FR)\\ Y_{i}=Y\_axis+rand(FR)\end{array}\right. \tag{13}\]  
Step 1.3: Because of the unknown location of the food, the distance to the origin of coordinates (\(Dist_{i}\)) and the judgment value of smell concentration (\(S_{i}\)) are calculated as follows:  
\[Dist_{i}=\sqrt{X_{i}^{2}+Y_{i}^{2}},\,S_{i}=1/Dist_{i} \tag{14}\]  
Step 1.4: The fruit fly with maximum smell concentration among the fruit fly group searches food according to the smell concentration judgment function (or called fitness function), which represents as follows:  
\[Smell(i)=function(S_{i}),\,[bestsmell,\,\,bestindex]=max(Smell(i)), \tag{15}\]  
where _bestsmell_ donates the maximal smell concentration, _bestindex_ is the corresponding fruit fly number and _Smell_ is the smell concentration of the group.  
Step 1.5: The new smell concentration is compared with the previous best smell concentration; if it is better than the last generation, the current best location and smell concentration can be presented as follows:  
\[smellbest=bestsmell,\,\left\{\begin{array}{l}X\_axis=X(bestindex)\\ Y\_axis=Y(bestindex)\end{array}\right., \tag{16}\]  
Otherwise, repeated Step 1.2 to Step 1.4 to find other better smell concentrations.  
Step 1.6: When the smell concentration reaches the preset precision value or the iteration number reaches the maximal _IN_, the circulation stops. Otherwise, repeat the process from Step 1.2 to Step 1.5.
# Fully Metallic Additively Manufactured Monopulse Horn Array Antenna in Ka-Band
## 5 Future Research Lines and Applications
### Enhanced Monopulse Arrays for Difference Pattern Applications  
The difference radiation pattern produced by this array design is critical in applications requiring high-precision directional control. Monopulse antennas are used extensively in radar systems for real-time target tracking, in MIMO communication systems for optimized signal reception, and in radio astronomy for capturing celestial signals with high directional accuracy. The flexibility provided by AM allows for intricate designs that can integrate advanced monopulse features, such as fine-tuned phase and amplitude differences across array elements. These features contribute to improved beam-steering and direction-finding capabilities, which are especially valuable in target-tracking applications and satellite communications.  
Future research could expand on the current design by incorporating adaptive tuning elements or multi-band capabilities, allowing a single array structure to operate effectively across multiple frequency bands or in reconfigurable scenarios. This would further exploit AM's ability to handle complex internal designs that integrate electronic components or embedded waveguides, enhancing the antenna capability to different communication standards.
## 2 Materials and Methods
### Analysis at the Material Level
#### 2.1.1 Application of the HFM Measurement Method
\begin{table}
\begin{tabular}{c c c c c} \hline \hline s & \(\Delta\)T & \(\varphi_{\text{tot}}\) & \(\varphi_{\text{cond}}\) & \(\varphi_{\text{rad}}\) & \(\varepsilon\) \\ \hline
**[mm]** & [\({}^{\circ}\)C] & [W/m\({}^{2}\)] & [W/m\({}^{2}\)] & [W/m\({}^{2}\)] & [-] \\ \hline
12.48 & 15 & 67.70 & 31.33 & 36.37 & 0.432 \\
9.82 & 15 & 75.25 & 39.82 & 35.43 & 0.420 \\
7.49 & 15 & 87.43 & 52.23 & 35.20 & 0.417 \\
4.98 & 15 & 113.20 & 78.55 & 34.65 & 0.410 \\
12.48 & 10 & 45.15 & 20.88 & 24.26 & 0.433 \\
9.82 & 10 & 50.17 & 26.54 & 23.63 & 0.421 \\
7.49 & 10 & 58.30 & 34.79 & 23.51 & 0.418 \\
4.98 & 10 & 75.63 & 52.42 & 23.20 & 0.412 \\
12.48 & 5 & 22.51 & 10.44 & 12.06 & 0.430 \\
9.82 & 5 & 25.01 & 13.27 & 11.74 & 0.418 \\
7.49 & 5 & 29.10 & 17.40 & 11.70 & 0.416 \\
4.98 & 5 & 37.72 & 26.18 & 11.54 & 0.410 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Experimental results: Specific heat flow \(\varphi\) and emissivity \(\varepsilon\) for different temperature difference and air gap thickness. Figure 4: (**a**) Total specific heat flow; (**b**) Radiative specific heat flow (\(\Delta\)T = 15 \({}^{\circ}\)C).