esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results Analysis and Discussion  
### Experimental Data  
Tianjin Port, as show in Figure 7, the largest comprehensive port in northern China, experiences heavy vessel traffic and complex navigation conditions. Vessels primarily access the Tianjin New Port area through several channels: the Tianjin Port main channel, the Zha Dong channel, the 300,000-ton channel, and the small vessel channel. Along these channels, there are seven recommended entry and exit positions for vessels. Depending on the vessel's draft, different entry and exit positions are chosen. The general principle is to minimize the vessel's occupation of the channel, with deeper-draft vessels using positions farther from the port and shallower-draft vessels using positions closer to the port. For the analysis, historical AIS data from the Tianjin Port channel area was selected. The data covers vessel movements from January 1 to 5 January 2021, during which approximately 100 vessel movements occur daily. The initial dataset used for training the navigational traffic behavior model included 222,623 trajectory points from 333 vessels. After data preprocessing, the final dataset consisted of 190,999 AIS trajectory points from 220 vessels. Given that the data collection period spanned 5 days, the same vessel may have multiple trajectories, including both inbound and outbound routes. In total, the training dataset includes 359 trajectories, with 205 being inbound and 154 being outbound. By ship type, there are 88 container ships, 93 cargo ships, 24 oil tankers, and 15 other ship types.  
The distribution of data regarding ship length, width, draft, speed, length-to-width ratio, and width-to-draft ratio is shown in Figure 8. The distribution of ship lengths ranges between 40 and 260 m, with the highest frequency observed around 170 m. Ship widths are primarily between 12 and 34 m, with the most common width being approximately 33 m. Draft range from 2 to 15 m, with the most frequent around 5 m. The SOG displays multiple peaks, particularly between 7.5 and 12.5 knots. The length-to-breath ratio (L/B) predominantly falls between 5 and 8, peaking around 6 and 7. The breadth-to-draft ratio (B/D) shows a broad distribution, with a notable peak around 4, indicating that most vessels have a width roughly 4 times their draft depth.  
The AIS data were divided into two sets, with 80% used as the training dataset and 20% as the test dataset.  
Figure 7: Research area (Tianjin Port).
# ICT Adoption and Stock Market Development: Empirical Evidence Using a Panel of African Countries
## 5 Research Findings and Discussion
### Correlation Analysis  
The correlation matrix is presented in Table 5. There are a number of relationships that are noteworthy. By and large, the stock market development measures are positively associated with ICT adoption measures as well as the financial freedom variable. This is in line with a priori expectations. Firstly, the stock market capitalisation variable (SMC) exhibits positive association with all four measures of ICT adoption. This implies that the higher the level of ICT adoption, the higher the stock market capitalisation. The highest degree of association of the stock market capitalisation variable is observed in its relationship with the number of fixed telephone users variable, with the level of association of 37.2% and which is highly significant. The stock market capitalisation variable is also positively associated with the financial freedom measure. This means that the higher the degree of financial freedom, the higher the stock market capitalisation. Secondly, the stock market turnover ratio (SMTR) variable is positively associated with a number of ICT adoption measures, namely broadband, fixed telephone and mobile-telephone.  
Its degree of association is highest with the fixed telephone variable, explaining 85.3% in the relationship, whilst the broadband variable has a 53.2% explanatory power. Thirdly, the stock market total value traded variable is positively associated across all four measures of ICT adoption. This implies that the higher the level of ICT adoption, the higher the value of the transactions traded on the stock exchanges. Fourthly, the number of listed companies variable is positively associated to the Internet users variable, and the financial freedom variable. This is in line with expectations. Lastly, all the stock market development variables are positively correlated to the gross domestic product variable.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Variables** & **Observations** & **Mean** & **Standard Deviation** & **Minimum** & **Maximum** \\ \hline
**NLC** & 109 & 8.28 & 14.56 & 0.87 & 59.36 \\
**SMC** & 110 & 49.12 & 65.15 & 7.24 & 328.36 \\
**SMTV** & 110 & 9.98 & 22.74 & 0.14 & 123.25 \\
**SMTR** & 110 & 12.36 & 14.71 & 1.08 & 82.88 \\
**FFI** & 110 & 0.52 & 0.12 & 0.3 & 0.7 \\
**NBU** & 110 & 507,576 & 895,321 & 320 & 5,223,311 \\
**NFTU** & 110 & 1,448,491 & 2,524,060 & 35,000 & 11,900,000 \\
**IU** & 110 & 27.66 & 16.96 & 1.9 & 61.76 \\
**NMU** & 110 & 36,400,000 & 38,100,000 & 1,033,300 & 154,000,000 \\
**GDP** & 110 & 121,000,000,000 & 146,000,000,000 & 8,490,000,000 & 568,000,000,000 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Summary statistics.  
All the associations are highly statistically significant. This lends credence to the view that stock market development fosters economic growth.
# The Importance of Context Awareness in Acoustics-Based Automated Beehive Monitoring
## 1 Introduction
From a geographical perspective, most contributions have come from the USA, UK, Japan, Slovenia, and Italy. From partially tropical countries (e.g., Mexico), experiments have mostly focused on the detection of the queen bee in _Apis mellifera amrica_ hives [43; 44]. For a more detailed overview, the interested reader is referred to [24]. One great benefit of acoustic beehive monitoring is the potential for real-time continuous monitoring, which may enable the detection of certain critical and rare events, such as queen piping [45; 46]. Continuous beehive monitoring may also enable new insights into increased mortality rates observed over the last decade [47; 48; 49; 50; 51; 52], which has been hypothesized to be linked to multiple stressors [53; 54]. Despite the burgeoning of acoustics-based beehive monitoring applications, as the recent review in [24] showed, existing tools rely on conventional audio features that have been developed for speech processing, namely root mean square power (RMS), mel frequency cepstral coefficients (MFCCs) [55], spectrogram, and features based on the discrete wavelet transform (DWT). It is widely known within the audio processing community, however, that such parameters can be extremely sensitive to environmental factors, such as ambient noise and background speakers. As such, noise suppression and/or characterization of the background noise (known as context-awareness) are needed for the development of accurate and replicable systems (e.g., [56; 57]). This will be particularly crucial for urban hives, which are on the rise [58], where loud and various urban sounds interfere with the internal hive sound recordings. In fact, while most published studies have shown the benefits of using the acoustic signal for hive health monitoring, the majority have relied on data collected over a short period of time (e.g., 24 h), usually in the months of June and July, when rain is possible, or were collected in remote regions in the countryside; thus, they may not have been exposed to certain environmental factors known to be detrimental to the quality of audio recordings. As such, it is not clear what the impact of such events is on audio-based precision beekeeping. This paper aims to fill this gap. Acoustic data were recorded from 11 urban beehives (one was intentionally left empty) during a three-month period. The effects of three environmental factors (rain, urban sounds, and beekeeper speech) were explored on the three most popular audio features described above. To quantitatively measure the impact of such factors on system performance, results for a beehive strength prediction model are reported and drops in accuracy were measured, to validate the claim that context awareness is crucial for automated beehive monitoring systems.
###### Abstract  
The aim of this study was to evaluate the learning curve of robotic thyroid surgery with regard to both operation time and temporary hypoparathyroidismism using quantitative statistical analysis. A total of 194 patients who underwent total thyroidectomy and concomitant central compartment node dissection for papillary thyroid carcinoma by a single surgeon between December 2008 and September 2017 were enrolled. The learning curve for operation time was assessed using the cumulative sum (CUSUM) technique, and the number of procedures required to reduce the incidence of temporary hypoparathyroidismridism to less than 30% was determined using the CUSUM and risk-adjusted CUSUM (RA-CUSUM) techniques. The learning curve for operation time was divided into three phases: phase 1 (the initial learning period, 1 st-19 th cases), phase 2 (the challenging period, 20 th-121 st cases), and phase 3 (the competent phase, 122 nd-194 th cases). To reduce the incidence of temporary hypoparathyroidismridism to \(<\)30% required 119 cases, and after adjustment for potential risk factors by RA-CUSUM analysis this extended to 173 cases. Technical proficiency for robotic thyroid surgery with respect to the avoidance of surgical complications probably requires a longer learning period than that required for operation time.  
learning curve; robotic thyroid surgery; papillary thyroid carcinoma; total thyroidectomy; transient hypoparathyroidismridism +
Footnote †: journal: Applied  
as, blood loss, surgical failure, perioperative complication, and others were not included. Moreover, only the moving average method was used and clinicopathological risk factors that might affect the learning curve were not considered.  
In this study, we aimed to evaluate the learning curves of robotic thyroid surgery for operation time and surgical complications using quantitative statistical analysis in a cohort of papillary thyroid carcinoma (PTC) patients who underwent robot-assisted total thyroidectomy (TT) and concomitant central compartment node dissection (CCND).
## 3 Results
### The Spatial Aggregation Characteristics of EEQ  
The value of Global Moran's I ranges from \(-1\) to \(1\); if the value is less than \(0\), the spatial autocorrelation is negative, and the greater the value, the stronger the autocorrelation. If the z score is larger than \(1.65\), the spatial distribution of geographic elements is clustered. From 1995 to 2019, the Global Moran's I values were 0.811, 0.818, 0.816, and 0.805 and the z scores were 213.707, 215.718, 214.982, and 212.191, respectively, indicating that the spatial distribution of EEQ not only was clustered but also had a strong positive autocorrelation. Therefore, kernel density estimation was employed to delve deeper into the spatial distribution characteristics of _RSEI_ hot spots in each EEQ grade.  
Figure 3: Spatial distribution of the EEG from 1995 to 2019.  
Table 5 presents the maximum kernel density values across different EEQ grades for the years 2019, 2010, 2000, and 1995. Notably, the maximum kernel density values in the moderate and good grades far outweighed those in other grades, indirectly reflecting that the majority of the study area was classified as moderate or good. Additionally, from 1995 to 2019, the change in the maximum kernel density values for the worse and poor grades followed a comparable trend, first increasing and then declining; this reinforced the observation that EEQ in the study area deteriorated until 2000 and then recovered by 2019.  
Figure 4 delineates the spatial distribution of the kernel density for the EEQ, highlighting a multi-core pattern. Notably, the spatial distribution of the kernel density for the EEQ between the moderate and good grades showed a contrasting trend from 1995 to 2019. The spatial distribution of the kernel density for the moderate grade was notably located in the towns within Ting River Watershed, such as Datong, Tingzhou, Cewu, Hetian, and Sanzhou. Conversely, the spatial distribution of the kernel density for the good grade was observed in the peripheral areas surrounding the study area, predominantly covering the land use types of forests, woodlands, and so on.
## 2 Types of Flexible Wearable Antennas
### Polymer-Based Antennas  
Flexible substrates were successfully implemented in circuits in the 1980s, which involved the development of the IoT and wearable polymer-based flexible antennas. This study investigates the radiation characteristics of flexible polymer antennas under bending and shaping conditions, testing five polymer-based substrates: polyimide (PI), polyethylene terephthalate (PET), polydimethylsiloxane (PDMS), polytetrafluoroethylene (PTFE), and liquid crystal polymer (LCP). These polymers collectively constitute approximately 80% of polymer-based FSSs, flexible antennas, and RFID tags [23]. A powerful rectenna does not use impedance matching or body loss; instead, it uses a small, conformal tattoo-polymer loop antenna with a 3 \(\times\) 3 FSS. This tattoo-polymer antenna enhances the performance of digital watches, enabling a 59% improvement in Wi-Fi and mobile hotspot charging efficiency [24]. Additionally, experiments are underway with new polymer composite antennas incorporating 45% to 50% conductive materials, demonstrating successful electromagnetic shielding at GHz frequencies. These antennas utilize a combination of composites, polymers, and conductive fabrics to optimize radiation properties. Testing confirms maximum gains of \(-10\) dB and \(-5.5\) dB across various frequency bands [25]. A compact, lightweight, flexible, and cost-effective patch antenna was also developed for smart glasses and wireless communication. Enhanced simulations using CST microwave studio software preceded its manufacturing and measurement stages. A robust theoretical and experimental reflection coefficient exists for 2.45, 3.5, and 5.20 GHz resonance frequencies, achieving gains of 1.91, 1.98, and 1.87 dB, respectively. Additionally, omnidirectional radiation patterns were observed for both bent and unbent configurations, with unbent patch antennas effectively conforming to cylinders with diameters of 40 mm, 25 mm, and 60 mm [26].
## 3 Results and Discussion
### Incubation Time and Equilibrium Temperature Effects  
Time of incubation and temperature at which equilibrium is attained were also optimized. The temperature was investigated within the range 20-80 \({}^{\circ}\)C. The obtained results clarified that the recovery of Pb\({}^{2+}\) ions reaches its optimized value in the range of 50-70 \({}^{\circ}\)C. Above 70 \({}^{\circ}\)C, the extraction efficiency decreases. This is probably due to instability of the complex formed between Pb\({}^{2+}\) ions and DLNL. This could decrease the efficiency of extraction. So, 70 \({}^{\circ}\)C was chosen as an optimized temperature for all subsequent measurements. Investigation of the incubation time within the range 5-30 min was carried out, in which the analytical signal was completely based on the incubation time. Incubation for 10 min was selected as an adequate time for all subsequent measurements.
# Multidisciplinary Reliability Design Optimization Modeling Based on SysML
## 5 Evaluation and Discussion
### Discussion  
Table 4 presents the optimization results for the traditional CO algorithm, the SysML-CEA algorithm, and the SysML-RBMDO approach applied to the in-vehicle environmental control integration system. Figure 19: XML file obtained from SysML optimization model transformation. Figure 18: Optimization problems for in-vehicle environmental control integration system. From Table 4, it is evident that the SysML-RBMDO method significantly outperforms both the CO and SysML-CEA algorithms in optimizing total mass. The SysML-RBMDO approach reduces the total mass by 8.80 kg compared to the CO algorithm, representing an improvement of approximately 10.8%. Compared to the SysML-CEA algorithm, the reduction is 5.78 kg, or approximately 7.4%. This section discusses the implications of extending SysML for multidisciplinary optimization (MDO) and reflects on the effectiveness of the proposed modeling approach based on evaluation results and case studies. The extension of SysML to include optimization variables, constraints, and objectives represents a significant advancement in handling complex Multidisciplinary Design Optimization (MDO) problems [30]. Building upon previous research, which primarily focused on basic SysML applications, our work introduces comprehensive metamodels for optimization variables, constraints, and objectives. This extension provides a clearer and more structured framework, improving both the clarity and manageability of optimization issues. By enabling the precise representation of various optimization scenarios, our approach enhances the integration of system design with optimization processes, facilitating a more holistic and effective analysis across multiple disciplines. Traditional optimization modeling methods often struggle with the integration and management of complex problems. Our research addresses these challenges by offering a more consistent and integrated SysML-based approach. Previous methods typically lacked the ability to effectively capture constraint expressions and interactions between variables [15]. In contrast, our use of SysML's parametric diagrams simplifies the definition and analysis of optimization problems. Additionally, the implementation of an XML-based information extraction method in our approach boosts model flexibility and scalability, streamlining data processing and enabling efficient integration with other tools. This advancement reduces the complexity of model design and enhances the overall manageability of the optimization process, distinguishing our work from earlier approaches. This study's application of the SysML-based optimization model to the in-vehicle environmental control integration system validates the practical effectiveness of our proposed method. While previous research laid the groundwork for SysML applications, our work extends these foundations by defining detailed system-level optimization objectives and subsystem-specific goals. This approach demonstrates how effectively our method
## 3 Arctic Shipping Risk  
### Life-Safety and Environmental Consequences  
Evaluating life-safety and environmental consequences related to Arctic shipping risks is challenging. A lack of accident data and experience limits the application of conventional risk approaches that rely on empirical event probabilities and quantified consequence severities. Alternative, unconventional risk assessments are necessary.  
[PERSON] et al. [22] used qualitative, expert-based risk analysis of ship accidents to establish risk levels for a range of vessel types and incidents in various regions of the Arctic. They established that the perceived likelihood of high consequence events increases with increasing vessel traffic, the number of passengers, and the presence of hazardous cargos. They highlighted that the severity of life-safety and environmental consequences can escalate in the Arctic due to a lack of emergency response resources and the harsh environmental conditions.  
Oil spills are the dominant threat posed by Arctic shipping [8] but evaluating environmental consequences is complex. The presence of dangerous goods onboard a vessel introduces the risk of environmental damage, but the consequence severity is not simply a product of accident potential and oil spill trajectory [23]. An evaluation of environmental risk from an oil spill should consider habitat exposure areas, recovery potentials of species and habitats, and the current state of the habitats [23; 24]. [PERSON] et al. [25] go further, suggesting that risk assessments must consider the entire ecosystem (rather than species-specific) to identify long-term impacts and provide a holistic understanding of the impacts of an oil spill. Given the complexity of Arctic oil spills, evaluating oil spill risk requires multidisciplinary expert knowledge and region-specific analyses.  
Evaluating life-safety consequences of Arctic shipping is also complex, with many dynamic factors (spatial and temporal). The number of passengers and crew on board a vessel and the ability to mount safe and effective escape, evacuation, and rescue (EER) will influence the severity of potential life-safety consequences. The rescue of crew and passengers is daunting: Limited regional search and rescue capabilities, scarce and aging infrastructure, long response times, and inadequate emergency response capacities for large-scale incidents (e.g., large cruise vessels present a high life-safety risk in the Arctic) [22; 26; 27].  
Risk-based operational decision-making for ice class vessels should be based on a careful consideration of all consequences and the integration of multidisciplinary knowledge. Evaluating the severity of environmental and life-safety consequences is complex with many dynamic factors. The framework proposed here integrates multidisciplinary knowledge for scenario-based risk management for ships operating in ice.
## 4 Evaluation
### Case Study  
We defined the study question using \"how\" and \"why\" questions and defined the case study proposals that must be evaluated to satisfy the study question [32], which is as follows.  
Study Question: How can and why does the proposed method recommend and help users meet security requirements?  
To answer the study question, we subdivided it into general proposals (GPs) and specific proposals (SPs).  
* Through the proposed ontology and process, the results can be used to analyze and understand APT characteristics, and security requirements can be recommended by retrieving cases that are similar to the scenario.
* To recommend useful security requirements, we can retrieve cases similar to the scenario and reuse the security requirements contained in these similar cases.
* The user may receive the result of analyzing the APT characteristics through the relationship of elements configured in the CB-PDO.
* Similar cases can be retrieved and explained using similarity metrics that reflect the characteristics of the APT.
* Depending on the given environment and constraints, users can retrieve cases in which a particular characteristic stands out by strongly weighting one particular characteristic.
* Users can review and manage the recommended security requirements to solve current problems using similar cases.  
To evaluate whether the defined study goal was satisfied, several analyses were performed, as summarized in Table 6. We defined the evidence needed to meet each  
Figure 6: Utilization value of the retained case.  
study proposal and study criteria to prove they are met, as described in the process of the proposed method. For the analysis, we designed a prototype using Java, and a screenshot of the program is shown in Figure 7. Other processes were described through an analysis of the study proposition.