esa-sceva/satcom-chunk-collection huggingface dataset:
# TC-Verifier: Trans-Compiler-Based Code Translator Verifier with Model-Checking
## 5 Conclusions  
This study presents a novel approach named \"TC-Verifier\" to verify trans-compilers using the Uppaal model checker to assess grammar rule compliance for high-level code translations. The verification of variable, function, class declarations, and while statements showed promising accuracy, with specific limitations observed in unsupported grammar elements and complex function bodies.  
These findings underscore the practical importance of formal verification in code translation, providing an alternative to traditional evaluation methods that rely solely on output similarity measures. By ensuring grammar rule compliance, this approach could significantly improve the reliability of trans-compilers used in the industry.  
Despite these contributions, this study faced limitations, including the complexity of encoding certain data types and the partial coverage of grammar rules. Furthermore, Uppaal's constraints on string handling presented challenges that necessitated workarounds.  
Future work could address these limitations by automating grammar rule encoding and exploring model-checking tools with expanded data-handling capabilities. Additionally, leveraging machine learning models to assist with automated modeling could streamline the verification process and reduce manual effort. Fine-tuning LLMs for filling the formally identified gaps of the trans-compiler translators and integrating both solutions will result in improved code-to-code translators. However, verifying LLMs will open new research questions.  
This research marks an important step towards reliable, formally verified code translation between high-level languages. As further developments in formal verification methods are implemented, trans-compilers can become even more reliable, supporting safer and more consistent code translation in a variety of software development contexts.  
Conceptualization, A.T.M., W.M., A.H.Y., H.Z. and N.E.; methodology, A.T.M., A.H.Y., and N.E.; investigation, A.T.M.; resources, N.E.; Software, A.T.M.; writing--original draft preparation, A.T.M.; writing--review and editing, S.S., N.E., W.M., H.Z. and A.H.Y.; visualization, A.T.M., A.H.Y. and W.M.; supervision, N.E., W.M., S.S., A.H.Y. and H.Z.; project administration, W.M. and N.E. All authors have read and agreed to the published version of the manuscript. Open Access Funding by TU Wien.  
The raw data supporting the conclusions of this article will be made available by the authors on request. This work was supported in part by the OEAD organization grant No. P017-2022. The authors of this paper express their gratitude to [PERSON], Head of Research Unit Compilers and Languages at TU Wien, for their valuable review of this article. The authors declare no conflicts of interest.
# UAV Multispectral Imagery Can Complement Satellite Data for Monitoring Forest Health
## 2 Methods
### Study Site  
As described in [12], the study site was located in Kinleith Forest in New Zealand's Central North Island (Figure 1) (Latitude 38\({}^{\circ}\)24\({}^{\prime}\)18.74S, Longitude 176\({}^{\circ}\)0\({}^{\prime}\)59.28E), approximately 28 km south-east of the town of Tokoroa. The site elevation is approximately 230 m and slopes gradually up towards the south-eastern corner of the trial. The site experiences a temperate maritime climate (total annual rainfall = 1238 mm, mean annual temperature = 13.4 \({}^{\circ}\)C) and the soils are loam belonging to the Kairanga series [52]. The trial area of interest was 2.7 ha and was located within a 7.3 ha stand of _Pinus radiata_ D. Don (_P. radiata_) planted in July 1993. Site preparation was via V-blading and the site was in its second rotation under plantation forest. Stand density at planting was 635 stems/ha (4.5 m \(\times\) 3.5 m). No thinning was undertaken and trees that suffered mortality early in the rotation were replaced. The site contained 35 rectangular (0.04 ha) plots that were part of a now defunct fungicide spray trial into disease resistance in immature trees. The fungicide spray trial was completed before age 6 (1999) whereafter the trees were left to grow. At the initiation of this study, a comprehensive health survey of the site showed no evidence of disease expression and the majority of trees were in good health. The study trees were mature and large (mean diameter at breast height = 462 mm, mean top height = 43.5 m) at the time of data collection and were harvested soon after the conclusion of this research.
# Internet of Things Botnet Detection Approaches: Analysis and Recommendations for Future Research
## 5 Analysis
### RQ3: What Methods and Techniques Are Utilized to Detect IoT Botnets?
#### 5.3.5 Signature-Based Methods  
The signature-based methods retain databases of known intrusion techniques (attack signatures) and detect intrusion by comparing behaviors to the database. They accurately detect known attacks and require less resources to detect intrusions. They have the disadvantage of being ineffective at detecting unknown or emerging attacks.  
The authors of [79] suggested a cloud-based system termed CloudEyes that is resistant to malware and offers effective and secure services for resource-concentrated devices. For cloud servers, CloudEyes, introduces suspect container cross-filtering, a new signature identification method founded on a mutable plan framework that offers fair and precise identification of signature malicious parts. For the host, CloudEyes implements a lightweight scanning agent that uses signature fragments to significantly decrease the variety of precise fitting. In addition, by communicating, sketch synchronizing and modular hashing, CloudEyes guarantees both data privacy and low-cost communication. They tested the efficiency of the proposed solution through using both suspicious traffic on site and regular files. The findings showed that the methods in CloudEyes are efficient and realistic, and the approach could surpass other current systems with less time and interaction.
## 7 Implication and Conclusions  
The results of this study have significant implications when investigating susceptibility or vulnerabilities to cyber sextortion. It can be considered that the more vulnerable a person is online, the more at risk they are to cyber sextortion attacks as the lack of understanding of email design cues that cyber criminals apply can leave people more susceptible. Additionally, the lack of paying attention to these design cues, as well as poor email security habits, would allow further developments of sophisticated cyber sextortion attack techniques for extortion at an enterprise level [33; 34]. Overall, from the results of this study, security awareness and training programs must be designed in a manner that incorporates attention to email design cues and habits to minimize or mitigate vulnerabilities to cyber sextortion attacks both at individual and organizational levels.  
In conclusion, cyber sextortion attacks are on the rise and affect millions of people, especially with the evolving trends of \"Work from Home\" due to pandemics such as COVID-19, and the consumerization of the Internet of Things (IoT) [35; 36]. However, sextortion attacks and individual susceptibility to these attacks are dramatically understudied. As such, little is known about which aspects of cyber sextortion attacks are likely to cause victims to be susceptible to them. This study is one of the first to investigate message-related factors in cyber sextortion email design and its effect on individuals' susceptibility to being victimized by cyber sextortion attacks. Four email design cues were tested for their effect on cyber sextortion susceptibility--design cues that had previously been shown to affect susceptibility to phishing attacks. While not all design cues significantly increased susceptibility, the fact that they were all present in email designs to which participants were susceptible shows their importance in deceiving people into responding to cyber sextortion attacks. As such, message-related factors are an important focus for future research on cyber sextortion attacks, as well as control mechanisms to mitigate the risks of these malicious attacks.  
Conceptualization, B.P. and A.B.; methodology, B.P. and A.B.; software, B.P.; validation, B.P. and A.B.; formal analysis, B.P.; investigation, B.P. and A.B.; resources, B.P.; data curation, B.P. and A.B.; writing--original draft preparation, B.P.; writing--review and editing, B.P. and A.B.; visualization, B.P. and A.B.; supervision, A.B.; project administration, B.P. and A.B.; funding acquisition, B.P. and A.B. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Western Sydney University.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to ethical restrictions.  
The authors would like to thank the journal for the opportunity to publish an open access paper, and many thanks to the outstanding reviewers for their hard work and feedback.  
The authors declare no conflict of interest.
## 6 Conclusions  
We analyzed the performance of a dispersion maps with non-constant zero-crossing places and symmetric configuration with respect to midway-OPC applying into the dispersion-managed link with midway-OPC for 24 WDM channels carrying 40 Gb/s RZ data. The performances of 16 different dispersion maps were compared, varying both the launch power of WDM channel, the residual dispersion per each fiber span and the TRD of whole links. Also, the performances of the proposed 16 different dispersion maps were compared with that of the conventionally configured dispersion map.  
The best performance was achieved by using the dispersion maps of the fixed configuration with a residual dispersion of 400 ps/nm, and these dispersion maps were attributed to increase the power margin and the effective TRD of the whole link, regardless of the specific location of the zero-crossing of the cumulative dispersion and the shape of the dispersion distribution of the FSG. In addition, it was also confirmed that the rest dispersion maps can improve the power margin and effective TRD compared to the conventional dispersion map, if the residual dispersion per fiber span is optimally selected near 400-480 ps/nm.  
The important point obtained in this paper is that in the case of nonlinear distortion compensation through OPC, as the optical transmission system and optical link become more complex, the shape of the dispersion map must be symmetric with respect to the OPC, and there must be a lot of variation in the local dispersion profile depending on the optical transmission channel and link conditions. Although the dispersion maps proposed in this paper are complex and the analysis process was not easy, we hope that our research will help design high-capacity long-haul optical transmission links.  
Conceptualization, J.-P.C. and S.-R.L.; methodology, S.-R.L.; software, S.-R.L.; analysis, J.-P.C. and S.-R.L.; resources, S.-R.L.; data curation, S.-R.L.; writing--original draft preparation, J.-P.C. and S.-R.L.; writing--review and editing, J.-P.C. and S.-R.L.; visualization, S.-R.L.; super-vision, J.-P.C. and S.-R.L.; project administration, S.-R.L. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to Institutional regulations.  
The authors declare no conflict of interest regarding the publication of this paper.
## 1 Introduction
For this reason, multispectral Sentinel-2 and Landsat-8 data were implemented into the methodology to analyze thermal anomalies. This enabled us to map lava flows during eruptive phases at two active volcanoes (Karngetang 2018/2019 (I) and 2019/2020 (II), Krakatau 2018 (I)) in Indonesia. Furthermore, ash and tephra deposits following eruptions at Krakatau 2018 (II) and Agung 2017 (I) were mapped based on vegetation changes.
## 2 Theoretical Basis
### Calculation of Selected Functionals from the GGI Model
#### 2.2.4 The Difference between the Geoid Undulations and the Height Anomalies  
An exact formula can be used to determine the difference between geoid undulations and height anomalies, resulting from a comparison of normal (\(H^{N}\)) and orthometric (\(H^{o}\)) heights (Figure 2) e.g., [19]:  
\[N-\zeta=\frac{\overline{g}-\overline{\gamma}}{\overline{\gamma}}H^{o} \tag{18}\]  
where \(\overline{g}\) is the mean gravity between geoid and point \(P\) defined by (19), and \(\overline{\gamma}\) is the mean normal gravity between ellipsoid and telluroid defined by (20).  
\[\overline{g}=\frac{1}{H^{o}}\int_{0}^{H^{o}}gdH^{o} \tag{19}\]  
\[\overline{\gamma}=\frac{1}{H^{N}}\int_{0}^{H^{N}}\gamma dH^{N} \tag{20}\]  
Although the value \(\overline{g}\), which is used to determine the orthometric heights, can be calculated by various methods, its determination is difficult. In practice, this value is often calculated on the basis of Poincare and Prey reduction [4]. In this approach, the mean gravity (\(\overline{g}\)) can be calculated at point \(P^{\prime}\), lying in the middle height of point \(P\) in three steps:  
1. Remove the effect of topography from the gravity value at point \(P\);
2. Introduce the free air reduction moving point \(P\) down to point \(P^{\prime}\); and
3. Restore the effect of topography at point \(P^{\prime}\).  
The calculations can either use the full topographic reduction (13) or only take into account the so-called the Bouguer plate (steps 1 and 3) and use the real or normal gravity gradient in the free-air reduction (step 2).  
Using the GGI model, the value of \(\overline{g}\)) can be calculated directly at point \(P^{\prime}\) based on (9).  
Value \(\overline{\gamma}\) is in practice calculated at the middle height of telluroid (point \(Q\)) above the ellipsoid.
# In-Depth Analysis of GAF-Net: Comparative Fusion Approaches in Video-Based Person Re-Identification
## 5 Experimental Results
### Results on iLIDS-VID Dataset
#### 5.1.4 Analysis of the Concatenation Fusion Factor (\(\lambda\))  
In this section, we analyze the fusion factor (\(\lambda\)) of Equation (7), which determines the fusion of appearance and gait information through concatenation. Figure 2 demonstrates the impact of varying \(\lambda\) values on rank-1 accuracy for the three tested architectures, namely OSNet, PiT, and MGH.  
For the OSNet architecture, we can see its rank-1 accuracy increases with \(\lambda\) until it reaches \(\lambda=0.45\), with a rank-1 accuracy of 70.93%. This accuracy remains relatively stable, then decreases with higher values of \(\lambda\).  
For the MGH architecture, the rank-1 accuracy also increases with \(\lambda\)--but more slowly--until \(\lambda=0.54\), reaching an accuracy of 90%, then remaining stable with higher values of \(\lambda\).  
The PiT model provides high rank-1 accuracy without adding any gait information (\(\lambda=0\)). This accuracy slowly increases with increasing \(\lambda\) values, reaching 93% at \(\lambda=0.6\), beyond which it decreases.  
Figure 2: Impact of the fusion factor (\(\lambda\); varying from 0 to 1) on the rank-1 accuracy.  
In summary, the accuracy of all three architectures is increased by up to 10% by adding gait information. Our tests show that the best values of \(\lambda\) are in the \([0.4,0.6]\) interval.
# Quality of Experience in 6G Networks: Outlook and Challenges
## 5 Quality of Experience in 6G Networks
### Causal Inference  
How is it possible to infer the cause of change in the user's QoE? Moreover, what would be the best operational actions in response? As discussed above, user experience in 6G networks is predominantly a cyberphysical, multisensory experience. This means that the network usually delivers all or most of the user context. Conversely, many elements in the end-to-end view, possibly over many pathways, will come together in 6G to deliver the service.  
Generally speaking, there are three classes of impact factors (or IFs) that affect the QoE of service delivery [28, 68, 74]: human, context, and system. The first relates to what can be called the demographic composite that makes the user. These include age, gender, culture, personality, mood, and interest. Naturally, these are not static affects, and they are bound to change in time or space. Context amends human IFs with an understanding of the user's location, surroundings, time, activity, space co-occupants, technical affluence, and economic capability. Finally, system IFs are concerned with the content, media configuration, network status, and device (or gear).  
Minding the projected intricacy of 6G networks and the vast array of service alternatives that can be delivered (be it at the user or the enterprise levels), the need to examine the QoE's definition and usability becomes more apparent.  
Consider a crudely reduced model of the types of components that are involved in delivering a user experience, namely human, context, network, service, content, and equipment (or gear). The 6G network operator is concerned with understanding the network's influence on the change in the user's QoE. Alternatively, the interest may be in the service or the content for the service provider. If the QoE measures can pinpoint the network as the reason, further exploration would be needed into the network elements.  
A decomposition of the network may involve access, core, computing, intelligence, and security. Within each of these elements, there stands a possible cause within computing cloud or edge, or within intelligence, data, error modeling, or optimization, etc. The cause is not necessarily singular, and the interaction of several factors may have resulted in the QoE.  
Addressing this complexity calls for causal inference engines. The reference here is not for correlation engines, which, with human support, can help identify cause and effect. Instead, it is to the autonomous or algorithmized causal inference engines as described in [75]. These engines can identify the reason behind the user's QoE and trace the cause to manageable impact factors.  
The research on these engines is still in its early stages. Still, considering the expected computing and intelligence capabilities in 6G, it can be predicted that they will play a significant role in network management.
# Noise-Assessment-Based Screening Method for Remote Photoplethysmography Estimation
## 3 Method
### Model Training for Noise-Assessment-Based Pulse Signal Screening
#### 3.4.3 FT-Transformer  
Tab transformer utilizes a transformer block to process categorical embeddings and generate contextual embeddings [25]. The contextual embeddings are then combined with the numerical features and fed through a multilayer perceptron (MLP) for prediction. However, in order to address the limitation of utilizing numerical features only in the final layers, we propose a model called the FT-Transformer that incorporates numerical embeddings [26]. The FT-Transformer's encoder receives numerical data as a list and employs linear embeddings for numerical representation. The numerical embeddings have a dimension of 64, and the model consists of 3 transformer blocks and 6 attention heads. Both the attention layer and dense layer employ a dropout rate of 0.3. The numerical embeddings, along with the noise assessment token embedding, are processed by the transformer block, resulting in contextual embeddings that are then passed through the MLP for prediction. During model training, Adam optimizer was employed, mean squared error (MSE) served as the loss function, and root mean squared error (RMSE) was used as the evaluation metric. Furthermore, early stopping was implemented to determine an appropriate epoch for training.
# Review of Image-Based 3D Reconstruction of Building for Automated Construction Progress Monitoring
## 3 Technology Path of Image-Based 3D Reconstruction  
This section presents a comprehensive synthesis of the state-of-the-art in image-based 3D reconstruction. By categorizing these existing studies, a research map is summarized. Figure 1 illustrates the research map for image-based 3D reconstruction starting from data collection to progress reasoning. The upper portion categorizes the as-planned models which is ready before construction, including geometry models, and relationships. Correspondingly, the bottom portion illustrates the as-built models that is collected on the construction site and reflects the actual construction status, including images and point clouds. Through the interaction among the as-planned models and the as-built models, combined with other technologies, the construction process is inferred from the geometry-based, relationship-based, and appearance-based information. The process can be divided into six steps: image collection, 3D point cloud generation, image-to-BIM alignment, point cloud segmentation, point cloud semantic recognition, and progress reasoning. Table 11 in the appendix shows literature related to these steps. In the subsequent part, the reconstruction process will be described in detail and at length and the advantages and possible obstacles of the state-of-the-art methods will be analyzed.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Publication** & **Number of Articles** \\ \hline Advanced Engineering Informatics & 9 \\ Automation in Construction & 22 \\ IEEE Conference & 5 \\ ISPRS Journal of Photogrammetry and Remote Sensing & 5 \\ Journal of Computing in Civil Engineering & 4 \\ Journal of Construction Engineering and Management & 2 \\ Journal of Information Technology in Construction & 2 \\ Sensors (Basel) & 2 \\ Others & 15 \\ Total & 66 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Literature sources.  
Figure 1: Research map for image-based 3D reconstruction.
## 2 Instrument Design
### Monitoring and Control Systems  
In this sub-section, the auxiliary systems needed for thermal stabilization, temperature monitoring, instrument control, and data retrieval are introduced. All the information retrieved from these sub-systems, and the necessary commands to control them are sent to and received from an external host computer via Ethernet connection.