esa-sceva/satcom-chunk-collection huggingface dataset:
# An Empirical Study of the Code Generation of Safety-Critical Software Using LLMs
## 2 Backgrounds and Motivation
### Code LLMs  
The software code can be considered as a special language. It is evident that large language models with language understanding and generation capabilities have strong potential in code generation. The previously mentioned models, GPT-3, ChatGPT, GPT-4, PaLM 2, Claude 2, and Llama2, all possess the ability to generate code. In addition to general-purpose large language models, several dedicated code models have been developed, such as DeepMind's AlphaCode [22], Salesforce's CodeGen [23], CodeT5+ [24], Meta's InCodern [25], OpenAI, and GitHub's Codex [8]. They have performed exceptionally well on popular code completion benchmarks such as HumanEval [8] and MBPP [26]. Based on the current test results, GPT-4 remains at the forefront in code generation [27].  
The evaluation of code generation capabilities in large language models is an important issue. OpenAI introduced the HumanEval benchmark [8]. In HumanEval, a new evaluation set was released to measure functional correctness in synthesizing programs from docstrings. HumanEval evaluates functional correctness on a set of 164 handwritten programming problems, such as \"words_string\", \"is_prime\", \"add_elements\", \" vowels_count\", \"multiply\", \"even_odd_palindrome\", etc. The Mostly Basic Programming Problems (MBPP) dataset contains 974 programming tasks in Python [26]. The programming tasks range from simple numeric manipulations or tasks that require a basic usage of standard library functions to tasks that require nontrivial external knowledge, such as the definition of particular notable integer sequences. DS-1000 is a code generation benchmark with one thousand data science problems spanning seven Python libraries, such as NumPy and Pandas [28]. In 2023, OpenAI further proposed a new evaluation benchmark called EvalPlus. EvalPlus augments a given evaluation dataset with large amounts of test cases newly produced by an automatic test input generator, powered by both LLM- and mutation-based strategies. EvalPlus more accurately reflects the true performance of LLMs for code synthesis [9].  
Microsoft extensively tested the GPT model on GPT-4 for code generation in various areas such as LeetCode algorithms, visualization of IMDb data, 2D HTML game development, and graphical user interface programming. The tests demonstrated that GPT-4 is capable of coding at a very high level [7].
# A Survey of Public Key Infrastructure-Based Security for Mobile Communication Systems
## 3 A Survey of the Literature
### Review of PKI-Based Security for 3 GPP Systems
In addition, although MN's real identity is not exposed to adversaries, adversaries can also apply the unbroken short-term credential to trace the movement of MN. Therefore, this scheme failed to achieve privacy preserving. [PERSON] et al. [45] proposed handover authentication scheme between HeNB and eNB in LTE networks, it is supposed to be fast and secured handover authentication scheme to fit-in with all of the mobility scenarios in the LTE networks. In addition, it is there to provide a number of security features including perfect forward/backward secrecy (PBS/PFS). This scheme consists of two phases: the initial attached phase, which prepares for the next handover authentication, and the uniform handover authentication phase which is for mutual authentication and key agreement between the UE and eNB. The PKI is required to have effect in all of the network entities. It is possible for the network side to support PKI due to processing abilities, and on the user side, the authors observed that it is easy to achieve PKI by the deployment of Trust Environments. Though the proposed scheme has an influence on the current 3 GPP standard, it does not use the complex key management methods and also unifies all of mobility scenarios, and this property greatly simplifies the current handover processes, although it is still complicated to achieve and has high computational cost (15.372 ms) compared with the 3 GPP-LTE schemes (0.1668 ms). Meanwhile, it is relatively good compared with the cost in the works of [PERSON] et al. [44] which is (18.321 ms).
# Synthetical Modal Parameters Identification Method of Damped Oscillation Signals in Power System
###### Abstract  
It is vital to improve the stability of the power system by accurately identifying the modal parameters of damped low-frequency oscillations (DLFO) and controlling the oscillation in time. A new method based on empirical mode decomposition (EMD), stochastic subspace identification (SSI), and Prony algorithms, called synthetical modal parameters identification (SMPI) method, is developed by efficiently matching the modal parameters of DLFO which are acquired from the SSI and Prony algorithm. In this approach, EMD is used for denoising the raw oscillation signals thereby enhancing the noise resistance, and then using the SSI and Prony algorithms to identify the precise modal parameters assisted by parameter matching. It is demonstrated that the proposed SMPI method holds great accuracy in identifying full modal parameters including natural frequencies, damping ratios, amplitudes, and phase angles with simulated signals with known modal parameters and real-time signals from some power system case studies. The strategy of SMPI has effectively overcome the weakness of a single approach, and the identification results are promising to heighten the stabilization of power systems. Besides, SMPI shows the potential to troubleshoot in different fields, such as construction, aeronautics, and marine, for its satisfactory robustness and generalization ability.  
low-frequency oscillations; modal identification; stochastic subspace identification; Prony; parameter matching +
Footnote †: journal: Applied Sciences
###### Abstract  
Additive manufacturing (AM) presents significant cost savings and lead time reductions because of features inherent to the manufacturing process. The technology lends itself to rapid prototyping due to the streamlined workflow of quickly implementing design changes. Compared to traditional machining, AM techniques are simpler in execution for design engineers because they do not require detailed engineering drawings and they typically make use of the nominal geometry in computer models. A novel transonic fan casing assembly has been developed that makes use of AM inserts surrounding the rotor to provide an opportunity to cost-effectively change the corresponding flowpath. The rapid prototyping design philosophy developed from this work will allow for numerous experimental studies into the effects that different design parameters of casing geometries have on fan aerodynamic performance. A fan stage representative of a small turbofan engine was successfully tested with smooth-walled, additively manufactured inserts as a baseline case for future configurations. Before installing the 3D printed casing assembly, computational thermal stress analysis was performed to reduce the risk in implementation due to the demanding environment associated with the rotor. AM components and materials typically have nonlinear mechanical properties, adding to the complexity of the structural analysis. As part of the research, steady aerodynamic performance was measured over the entire relevant operating range of the fan.  
additive manufacturing; turbomachinery; fan aerodynamic performance +
Footnote †: journal: _Applied Sciences_  
manufacturing at scale with more flexible \"Engineered-To-Order\" components for specific design requirements as coined by [PERSON] et al. [3].  
AM is advantageous for components with high complexity, therefore it has seen increased use in turbomachinery research, where components are often complicated and require one-off pieces [3; 4]. The entire stationary diffusion system for an aero-engine centrifugal compressor was 3D printed using stereolithography (SLA) and successfully tested over the full operating range [5]. AM was also used successfully by the Naval Postgraduate School to implement a casing treatment on a transonic rotor [6; 7]. The individual passages of the treatment were 3D printed and then cast. It would be most cost-effective and take most advantage of the AM process to have 3D printed inserts that could simply be exchanged and installed after printing without any required machining or finishing operations. There is currently no such application until now. A novel fan casing assembly, known as the adaptable fan casing, was designed to make this workflow a reality.
## 3 Results and Discussion
### Correlation between BEPS-Simulated Crop GPP and Ground Measurements
[73] found that soybean has greater C rhizdeposition than maize, and the amount of C rhizdeposition varies greatly with soil fertility and organic amendment, presenting a challenge in using GPP for biomass mapping by BEPS or other crop growth models. Although non-linearity is shown between GPP and AGB of corn, correlation is still high (R\({}^{2}\) = 0.76) (Figure 4). This suggests that C3 models may be used to simulate GPP of C4 plants if some parameters are adjusted accordingly, although this is subject to further investigation. The correlations between LAI and crop AGB are shown in Figures S4 and S5. For all crop types, crop LAI explains only 50% of variation in crop AGB, significantly lower than that explained by crop GPP (Figure S4); this is because LAI only explains mostly the top part of total AGB; as crop structure varies, the non-leaf part the AGB has a significant difference; for example, corn has far more non-green AGB than the soybean does. This suggests that the cumulative GPP correlates better to AGB which is also a cumulative variable, than it does to the green LAI, which indicates the status of the crop. By crop type, the LAI variations of canola, oat, and wheat explain only 61%, 59%, and 0% of variations in their corresponding AGB, respectively. The LAI variations of black bean, corn, and soybean explain 94%, 81%, and 62% of the variations in their AGB, respectively, higher than that of canola, oat and wheat. This difference can be explained by the growing stages: unlike canola, oat, and wheat, the AGB of black bean, corn and soybean cover only the vegetative growth stage of crop phenology. This is evidenced by the stronger correlation between leaf biomass and LAI (R\({}^{2}\) = 0.55) than between AGB and LAI (R\({}^{2}\) = 0.32%) as shown in Figures S6 and S7. Ideally, the LAI should be highly correlated with leaf biomass. However, LAI values derived from Sentinel-2 are equivalent \"green\" LAls, resulting from the accumulation leaf pigments and leaf senescence [74]. Therefore, satellite-derived LAI correlates more with green biomass including green stems and fruits [75] and the R\({}^{2}\) of 0.55 is still considered to be high.
# Regeneration of Articular Cartilage Using Membranes of Polyester Scaffolds in a Rabbit Model
## 3 Results
### Histopathology  
#### 3.2.1 Differences in Membranes Performance  
Kruskal-Wallis tests were performed, for ratings provided by each histologist, in each time-point (at 8, 16, or 24 weeks), to examine the differences in recovery between the three groups: a group treated with the membrane PVP (\(n\) = 7; the PVP group), a group treated with the membrane Z (\(n\) = 7; the Z group), and the control group (\(n\) = 4).
# Packet Injection Exploiting Attack and Mitigation in Software-Defined Networks
## 2 Background and Related Works  
### Background  
SDN separates the control layer from the data layer of the network and replaces the original routing negotiation method with a centralized controller, which significantly improves the efficiency and flexibility of network management and control. Figure 1 shows a typical SDN network architecture consisting of the data plane, control plane, application plane, southbound, and northbound interfaces. The data plane is running for forward ing data packets according to specified rules or policies. The control plane maintains the resources, global topology visibility, and status information. The application plane interacts with the controller through the northbound application rpopgramming interface (API), facilitating the rapid advancement of services, such as network configuration and application deployment.  
Due to the centralized control, the topology management service in SDN is different from a traditional network. To promote network management, the OpenFlow controller maintains topology information and provides this visibility for upper-layer services/applications [7]. In SDN, topology management mainly includes switch discovery, host discovery, and link discovery. For host discovery, the controller tracks host location by maintaining the Host Profile. It listens to _Packet-In_ messages and indexes the Host Profile to handle host mobility.
# Overview of Mobile Communications in Colombia and Introduction to 5G
## 1 Introduction  
Ericsson's Mobility Report 2021 records 8.2 billion mobile subscriptions worldwide, including all major wireless technologies (CDMA, GSM, HSPA, LTE, and 5G) [1]. The same report shows that second-generation (2G) and third-generation (3G) connections are shrinking every year, and estimates that the use of fourth-generation (4G) technologies will peak in 2021, a year with the rapid growth of fifth-generation (5G) networks. In Latin America and the Caribbean, the trend is towards a decrease in 2G and 3G networks, while 4G and 5G networks are on the rise, like the situation in the rest of the world. Therefore, 5G Americas forecasts indicate that from 2022 onwards, mobile connections via long-term evolution (LTE) will be decreasing, contrary to what will happen with 5G [2]. In the case of Colombia, the country has the third-largest population in Latin America [3] and one of the leading economies in the region [4], which is reflected in several indicators, includingmobile telephony penetration, which reaches a rate of 70 per 100 inhabitants. [3]. For these reasons, it is important to know the current scenario of the mobile telephony market in Colombia since it plays an important role in the economic and social development of the country.  
This research details the cellular frequency bands operating in Colombia associated with their economic auction values and the companies that own them. It also identifies key technical issues and highlights the state's regulatory policy about mobile telephony. According to the academic literature reviewed, this is the first time that research of this type has been conducted, contributing not only to accelerating the implementation of the 5G telephony network that has not yet been offered commercially in Colombia but also by contextualizing national and international actors in this field of telecommunications from both industry and academia as a basis for research in the area of mobile technology and the socioeconomic impact of the country.
## 3 Quality Assessment of the BIC/B2a Signals from BDS-3 Operational Satellites
### Pseudorange Multipath and Noise  
The same as reference [7], we adopt the multipath (MP) combination to determine the pseudorange multipath and noise. For detailed definition of the MP combination, please refer to reference [7; 33], Figure 4 illustrates the MP combination against elevation for BDS-3 C20 (B1C/B2a/B1I/B3I signals) and BDS-2 C11 (B1I/B2I/B3I signals) with the iGMAS (top panels) and M300 Pro (bottom panels) receiver. In line with our previous results for BDS-3 experimental satellites [7], the MP combination against elevation series from both iGMAS and M300 Pro receivers show that the satellite-induced elevation-dependent code biases, which have been previously identified to exist in BDS-2 code observations [34], seem to be no more obviously present for BDS-3 operational satellites as well. Similar results are also observed in [3].  
Similarly, the Root Mean Square (RMS) values of the MP combinations are also calculated with elevation angle interval of 5\({}^{\circ}\), so as to further evaluate the quality of code observations among the various signals, and the results are shown in Figure 5. Consistent with our previous results [7], we observe that the RMS of MP combinations are clearly dependent on the satellite elevation angles for all signals. Using the iGMAS receiver, the RMS values for L1/E1/B1C are approximately 0.3 m close to the zenith and increase to approximately 1.0 m at low elevation angles. Nevertheless, the values are about 0.1 m close to the zenith and increase to approximately 0.5 m at low elevation angles for L5/E5a/B2a. Therefore, we conclude that the RMS values for L1/E1/B1C are obviously larger than L5/E5a/B2a. Similar phenomenon is observed for M300 Pro receiver, but with larger RMS values. Note that the RMS values for L1 is nearly identical with L5/E5a/B2a and much smaller than BIC/E1,  
Figure 3: Average _C/N\({}_{0}\)_ values against elevation for each available signal for the iGMAS (**a**) and M300 Pro (**b**) receiver.  
which is quite different from using the iGMAS receiver. We speculate that this may due to the specific hardware design of the M300 Pro.
# Mobility Management of Unmanned Aerial Vehicles in Ultra-Dense Heterogeneous Networks
## 7 Future Research Directions
### Mobility Management  
In future HetNets, managing UAV mobility will be a critical factor that requires thorough investigation. Due to their development features, UAV mobility poses a great risk since they rapidly move in 3D. The use of mm-wave groups in 5G and 6G systems is also a significant issue that adds to UAV mobility challenges. The massive expansion of UAVs and mobile connections will further create new problems since mass adjustment will be a significant task that necessitates a productive arrangement. The mobility management of linked UAVs must be properly addressed in future systems.
## 3 Preliminaries
### 2-Out-of-2 Additive Secret Sharing  
Additive secret sharing is implemented within a field \(\mathbb{F}\). A secret \(S\in\mathbb{F}\) is randomly divided into several shares. Additive secret sharing consists of the two algorithms **Share** and **Reconstruct**, for simple 2-out-of-2 secret sharing:  
\(\textbf{Share}_{2-2}:\) On input secret \(S\),  
* select \(s_{0}\in\mathbb{F}\) uniformly at random.
* set \(s_{1}=S-s_{0}\).
* output \((s_{0},s_{1})\).  
\(\textbf{Reconstruct}_{2-2}:\) On input \((s_{0},s_{1})\),
* Output \(s_{0}+s_{1}\).  
The above is a 2-out-of-2 additive secret sharing scheme. In this scheme, you must hold both \(s_{0}\) and \(s_{1}\) shares to reconstruct the secret \(S\). We can easily extend this into \(n\)-out-of-\(n\) additive secret sharing scheme. Similarly, all \(n\) shares must be available to reconstruct the secret.
## Materials and Methods
### Field Data Collection  
The field data collection was done in December 2014 along the land use gradient from Bushbuckridge communal areas, Sabie Sands and Kruger National Park, covering granite, gabbro and basalt geological types (Figure 1). The site selection process captured the nutrient contrast from low to high between granitic, gabbro and basalt derived soils, respectively, and along the rainfall gradient (east-west). To further ensure grass biomass variability, transects were laid out to sample both valley and crest land units. Grass biomass in the savanna ecosystems is also influenced by topography with valley areas generally having higher grass biomass than crest areas. Purposive and road sampling was done for placement of sampling plots since we could not penetrate deep into the savanna because of management restrictions. The 300 m buffers were created on both sides of the selected roads. Within the buffer polygons, random sample points were generated using the ArcGIS add-on, called Hawth tools. All the points falling on the road and open areas next to the road were rejected because of the unavailability of grass. A total of 30 plots were surveyed. Each randomly selected sample point was treated as a plot with a size of 20 m \(\times\) 20 m. To capture the variability in each plot, two subplots of size 50 cm \(\times\) 50 cm were used to collect data about the dominant species and grass samples. The grass samples were cut for chemical analysis to retrieve leaf N concentrations. Grass samples were dried at 80 \({}^{\circ}\)C for 24 h and were chemically analysed for leaf N (%) at the Bemlab, Strand, Western Cape South Africa [17].
## 4 Results and Discussion
### Comparison with the Existing Approaches by Varying the Number of Obstacles  
This scenario is comprised of 10 maps with varying numbers of obstacles in a \(W\) of 1 km\({}^{2}\) to analyze the impact on our PP method's performance from increasing the number of obstacles. The obstacles were clustered between \(s\) and \(t\) in such a way that all methods would avoid them during pathfinding. Figure 10 presents the results of our proposed PP method and a comparison with the other algorithms from varying the number of obstacles. When \(W\) enclosed more obstacles, the suggested method could quickly determine a good-quality and safe \(P\) from \(W\). It was better than the ApVL and RRT*-AB algorithms, based on the metrics, even when varying the number of obstacles in the CPS. The \(P\) determined by the proposed method was the shortest and smoother than the other two algorithms. Through simulation results and their comparison with previous methods on 10 obstacles' counts-based maps, the proposed method decreased the computing time for pathfinding by 27.06%, on average. For path lengths, the paths generated by our PP method, on average, were 4.6% shorter (i.e., produced at a lower cost) than the previous methods.
## 3 Methodology
### Stage 2:  
In addition, the DEMATEL method is utilized for analyzing and building a structural approach of a causal relationship between the identified barriers. The DEMATEL approach was established to resolve and learn the complex criteria and intertwined issues group in 1976. DEMATEL is a well-known methodology that is often used for the assessment of decision problems in Japan [86]. The DEMATEL illustrates the causal relationships among the causes and effects of various variables and provides a structural framework for the system. DEMATEL has a significant advantage over other models in that it enables producing potential findings with the minimum information [84]. Although few other approaches can also be used for the analyzing of factors, such as interpretive structural modeling (ISM) and analytical network process (ANP). In comparison to ISM, the DEMATEL method assists in the identification of contextual relationships between factors and emphasizes the impact of their interactive relations. Further, this approach also determines the proportion of the cause-and-effect relationships of the barriers [90]. The DEMATEL is useful for not only describing direct subsystem relationships but also for defining the degree to which the subsystems interact. Moreover, if we want to measure or evaluate the cause-effect interaction between subsystems, DEMATEL seems to be more useful than the ISM in the measurement of complex systems [87]. The DEMATEL approach not only transforms interdependency interactions into a cause-and-effect cluster via matrixes but also discovers the essential barriers of an intricate system of barriers with the aid of an impact association graph [91]. Researchers may use the DEMATEL approach to understand the conceptual interactions between the barriers used within the issue structure and to assess the determination of their cause-effect relationships, compared with other modeling approaches like total interpretive structural modeling (TISM), graph theory and matrix approach (GTMA), and ANP [92].