esa-sceva/satcom-chunk-collection huggingface dataset:
# Pointer Meter Reading Recognition by Joint Detection and Segmentation
## 3 Proposed Method
### Loss Functions  
To train our proposed deep model, we apply the widely used Intersection over Union (IoU) loss [55] for the task of bounding box regression and the cross-entropy (CE) loss for the dense prediction task. Specifically, we first optimize the weight parameters of the meter dial location network by minimizing the IoU loss and then train the reference point segmentation network using the CE loss, which is summed up over all the pixels. The IoU loss is defined as  
\[IoU(b_{1},b_{2})=\frac{b_{1}\cap b_{2}}{b_{1}+b_{2}-b_{1}\cap b_{2}}, \tag{2}\]  
where \(b_{1}\) and \(b_{2}\), respectively, denote the located bounding box of a meter and the corresponding ground truth, and \(b_{1}\cap b_{2}\) is the overlapping area of \(b_{1}\) and \(b_{2}\). The CE loss is formulated as follows:  
\[CE(p_{i},\hat{p}_{i})=-p_{i}\log\hat{p}_{i}-(1-p_{i})\log(1-\hat{p}_{i}), \tag{3}\]  
where \(\hat{p}_{i}\) represents the predicted label, and \(p_{i}\) refers to the ground truth. Note that, although various loss functions have been designed for detection and segmentation tasks, we found that the IoU and CE loss functions work well for our model.  
Figure 4: A diagram of different methods for computing the dial number.
## 3 Results and Discussion
### Model Validation  
This section presents our model validation using new data with nine data samples from the L & K mine of Monyova copper mines, as presented in Table 6. These new cases were used to validate the developed RBF-SVR model in this study. Figure 13 displays FOS results related to new data and the developed model. As can be seen, the RBF-SVR model has generally provided an acceptable performance against new data that have been practically recorded. According to Figure 13, five cases are very close to each other, i.e., (1.11, 1.17), (1.08, 1.16), (2.15, 2.06), (1.26, 1.19), and (1.24, 1.18). The other four cases have a bigger difference between new data and the developed model. It can be concluded that the performance of the developed model in this research offers a positive response for optimization analyses that require a high-precision model. The developed model is able to obtain the least error for optimal parameters.
## 4 Conclusions  
The results of the modified model find comparable agreement with those from previously published studies. The consideration of different diffusivities in the numerical calculation of hydrogen combustion is indispensable since the position of the high-temperature zone shifts 9.5 mm downstream towards the nozzle. Although the maximum achievable flame temperature is overestimated by about 4%, the new model nevertheless leads to a precisely local determination of the high-temperature zone. With the modified model, the positions of the high-temperature zones can be predicted in a better agreement with experimental measurements from previous studies than in the existing combustion model in OpenFOAM. Thus, a possible overheating of the nozzles and the hydrogen supply line material can be prevented. The comparison of varying \(\lambda\)-values and power shows that the air number significantly affects the flame structure and the distribution of the high-temperature zone. As the air number increases from stoichiometric combustion to \(\lambda~{}=~{}2\), the flame width decreases by 50%. A change in the input power of \(\pm\)50% leads to different temperature distribution in the entire combustion chamber and proportional varying length of the hydrogen jet. Both parameters cause a change in the reaction behavior during combustion. This paper shows that a simplified model assuming a single-step mechanism under the assumption of an infinitely fast chemistry model and a non-binary diffusion as well as without diffusion matrix gives comparable results to more complex models and can be used to determine the flame structure of hydrogen diffusion flames.  
Conceptualization, J.B., V.J. and A.D.; methodology, J.B. and V.J.; software, J.B.; validation, J.B. and V.J.; formal analysis, J.B., V.J. and A.D.; investigation, J.B. and V.J.; resources, V.J. and A.D.; writing--original draft preparation, J.B. and V.J.; writing--review and editing, J.B. and V.J.; visualization, J.B. and V.J.; supervision, V.J. and A.D.; project administration, [PERSON] and A.D.; funding acquisition, [PERSON] and A.D. All authors have read and agreed to the published version of the manuscript.  
This research was funded by German Federal Ministry of Economy and Energy (BMWi) through the Zentrales Innovationsprogramm Mittelstand (ZIM) program (Grant Number ZF4134317 AW9).  
Figure 9: Temperature and mass fraction for different input power; solid line: performance decrease; dotted lines: performance increase; dashed lines: initial power.
## 2 Background and Methodology
### Maturity Model  
Maturity models (MM) aim to assist organizations by providing guidance with their sequence of discrete maturity levels for a class of processes [5]. With their structural approaches, they offer a roadmap for the organization's improvement.  
The Capability Maturity Model Integration (CMMI) and Software Process Improvement and Capability dEtermination (SPICE) are a set of standards, i.e., ISO/IEC 330 xx, known as fundamental patterns in the assessment of process capabilities [5; 6; 7]. CMMI has been a major standard for software and systems development for more than 20 years. They can be used descriptively to assess the current process capability level. These models have been customized to different domains, including the automotive industry and government [8].  
The data management maturity model (DMM) consists six functional domains (data management strategy, data quality, data operations, platform and architectures, data governance, and supporting processes) and was developed using the principles and structure of CMMI [6]. The maturity model was introduced in [PERSON] et al. 2022 [9]. It provides an overview of the maturity level of data management in an organization [10; 11] with a strong master-data focus. Twenty-six capabilities are defined under six process groups to provide maturity levels with a relevance evaluation for creating an extensive roadmap for continuous improvement in a structured and repeatable way. Master data in that context are a specific set of data that describes the key business entities on which an organization's activities are based, such as business partners, products, or employees [12]. Moreover, objects of master data can be seen as official and basic business objects in companies that are used in value-adding processes [13].  
\begin{table}
\begin{tabular}{l l} \hline \hline \multicolumn{2}{c}{**Key Elements**} \\ \hline \multirow{4}{*}{Digital Transformation (K1)} & Strategy (C11) \\  & Data-driven culture (C12) \\  & Business ecosystem (C13) \\ \hline \multirow{4}{*}{Data Science (K2)} & IT Professionals (C21) \\  & Add value (C22) \\  & Competitive advantage (C23) \\ \hline \multirow{4}{*}{Data-Driven Organization} & Demand (C31) \\  & BM development (C32) \\  & Value creation (C33) \\ \hline \multirow{4}{*}{Data-Driven Innovation (K4)} & Big data (C41) \\  & R\&D (C42) \\ \cline{1-1}  & Business insights (C43) \\ \hline \multirow{4}{*}{Data Analytics (K5)} & Descriptive (C51) \\ \cline{1-1}  & Predictive (C52) \\ \cline{1-1}  & Prescriptive (C53) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Key elements of data-driven organizations ([PERSON] et al. [4]).
# Study on the Time Domain Semi Analytical Method for Horizontal Vibration of Pile in Saturated Clay
## 5 Conclusions  
This article uses the fractional order Kelvin model to describe the rheological properties of soil, considers small deformation to establish a coupled vibration model of saturated clay and pile foundation, and uses Laplace transform to solve the control equation to obtain a semi analytical solution in the time domain. Based on case analysis, the horizontal vibration characteristics of pile foundations in a saturated clay foundation were studied, and the following conclusions were summarized:  
1. The displacement and internal force response of pile vibrations in saturated clay foundations have a delayed effect. The stronger the rheological properties of the foundation soil, the more obvious the delay, and the lower the load frequency, the more significant the influence of rheological properties on the delay effect.
2. The stronger the rheological properties of the soil, the smaller the displacement amplitude of the pile foundation, and the higher the load frequency, the greater the decrease in displacement amplitude. The positive bending moment of the pile decreases with the increase in soil rheological properties, while the negative bending moment increases accordingly.
3. The shear force at the top of the pile is not affected by the rheological properties of the soil, but both the positive and negative shear forces of the pile body significantly increase with the enhancement of the rheological properties of the soil. Therefore,  
Figure 14: Vibration response of pile top shear force under different viscosity orders (\(\omega=2\pi,z=5\tau_{0}\)).  
Figure 15: Vibration response of pile shear force under different viscosity orders (\(\omega=2\pi,z=5\tau_{0}\)).  
when designing pile foundations in saturated clay, it is necessary to appropriately increase the pile diameter or increase the reinforcement to meet the shear performance.  
Conceptualization and methodology, X.R.; software and validation, L.-a.W. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Gansu Provincial Science and Technology Program Funding Project (No. 22 JR5 RA383).  
Not applicable.  
Data Availability Statement: Data are contained within the article.  
The authors declare no conflict of interest.
## 5 Conclusions  
This paper proposed an evaluation method for the site selection of photovoltaic (PV) plants, which used spatial analysis with a geographic information system (GIS) and visualized the plan view of the solar PV plant installations in a building-information model (BIM) environment for energy planning and management when constructing highway networks. The proposed method can investigate suitable sites that satisfy various criteria (e.g., distance to roads \(\leq\)200 m, slopes \(\leq\)15 deg, and not in river and reservoir regions) at a national and regional scale (a small district, Ucheon-myeon in South Korea). In addition, this study conducts a visualization of the installation of PV sites in highway network construction using GIS-based result data.  
The major findings and contributions of this study are summarized as follows. First, given the geo-spatial analysis, the proposed method can select optimal sites for PV plants within the vicinity of highway networks (200 m). Second, the spatial analysis can be used to discover the less intrusive regional areas where solar PV power generation can be implemented (e.g., see Table 2). Third, based on the result of changes in the range of PV production distribution, it was found that the regional scale affects solar PV power generation. Forth, the available regions for solar-plant installations analyzed from the GIS can be incorporated into solar-panel families in a 3D environment using an integrated GIS and BIM approach. Eventually, this approach will enable the transformation of evaluated solar PV output values, leading to the search for potential sites for PV-plant installation without regional features (i.e., level of complexity) for energy management in the maintenance of highway infrastructures (Figure 10).  
With the proposed method and visualization model, it is possible to find optimal sites for PV plants and visualize the feasibility of installing new PV plants in the vicinity of highway networks in a 3D environment.  
J.H.: Methodology, formal analysis, writing--original draft. H.M.: Conceptualization. S.C.: Writing--review and editing. S.H.: Conceptualization, supervision, writing--review and editing. D.-E.L.: Project administration and funding acquisition. All authors have read and agreed to the published version of the manuscript.  
This research was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. NRF-2018R1A5A1025137).  
Not applicable.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to the policy of the data provider.  
The authors declare no conflict of interest. The sponsors had no role in the design, execution, interpretation, or writing of the study.
# Firmware Updates over the Air via LoRa: Unicast and Broadcast Combination for Boosting Update Speed
## 4 Analytical Expression of the Total Update Time  
In this subsection, we include an analysis of the main considered KPI, i.e., the time required to update a project. The problem is to find an expression for the time required to correctly transfer \(M\) chunks of the firmware to each of the \(N\) nodes in the project. The analysis will be focused on the main part of the update, i.e., sending the firmware chunks. It should be noted that the airtime, i.e., the time in which the medium is occupied, is different from the total time required for the update, because the duty cycle imposes some limitations (e.g., only 1% of the airtime can be used). Therefore, after sending each frame, the nodes must calculate a time interval in which nothing can be sent to the air [9].  
In the analysis, we will consider a fixed transfer rate for the whole project, i.e., the gateway uses the same modulation and bandwidth for all the nodes. In the case of LoRa, this means that the gateway will use a fixed spreading factor and channel bandwidth.
# An Intelligent Fuzzy-Based Routing Protocol for Vehicular Opportunistic Networks
## 5 Conclusions  
This paper proposed the FCRP as a novel approach to enhance routing efficiency in OppNets. By incorporating fuzzy logic, the FCRP evaluates multiple parameters, including buffer occupancy, angle to destination, and the number of unique connections, to make intelligent and context-aware routing decisions. The protocol's performance was thoroughly evaluated using both the FuzzyC simulator and the ONE simulator.  
The results demonstrate that the FCRP exhibits competitive performance in key metrics such as delivery probability, average hop count, latency, and overhead ratio. The FCRP's adaptability to varying buffer conditions and node densities highlights its robustness in dynamic vehicular environments, demonstrating its efficiency in minimizing network congestion and resource consumption. For smaller networks, the FCRP outperforms both Epidemic and MaxProp across all metrics. Regardless of the network size, the FCRP achieves a significantly low overhead ratio and higher delivery probability than Epidemic in all scenarios. However, as the network size increases, the delivery probability of the FCRP becomes slightly lower than MaxProp, although their performance is comparable when considering all metrics. A limitation of the FCRP is its slight increase in latency as network size grows, which may not make it ideal for delay-sensitive applications. Additionally, in large networks, the delivery probability gap with MaxProp becomes more noticeable, indicating that the FCRP might not be the best solution despite its extremely low overhead.  
Future work could focus on optimizing the protocol to reduce latency and improve delivery probability in larger networks without compromising its low overhead. Furthermore, extending the protocol to consider real-time contextual factors, such as traffic patterns and energy constraints, could enhance its applicability in diverse networking environments. Overall, the FCRP demonstrates significant potential as an effective and resource-efficient routing protocol for OppNets, contributing to the advancement of reliable communication in dynamic and delay-tolerant systems.  
Conceptualization, E.Q. and K.B.; methodology, E.Q., P.A. and L.B.; software, K.B. and E.Q.; validation, S.H., K.M. and L.B.; writing--original draft preparation, E.Q. and K.B.; visualization, E.Q., S.H. and P.A.; supervision, L.B. and K.M. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
Data Availability StatementData are contained within the article.
## 3 Findings
### Discovering New Nursing Care Approaches
#### 3.1.1 Nurse Communication  
Patients perceived the bedside handover process as a structural improvement to enhance nurse-patient communication. They noticed a consistent occurrence of handover between nurses who kept them informed of their treatment without necessitating inquiries on their part. Patients who had a hospital stay a long time ago reflected on the changes they noticed, specifically regarding patient involvement in the handover process.  
..._I thought the communication is a lot better...._I like to be kept informed and up to date on what was happening with my treatment. And in this visit, I felt much better than in the past [when] I had to ask, and this time the nurses..._came and told me, though without asking I thought was, much, much better...._I was kept informed [and]... standard improvement..._this is what pleased me the most. (Patient 1)  
..._I thought that their handover, discharge procedure was in every way superior compared to the one we had in (name of another hospital)...._the behaviour the nurses had here,... they were very good. I was able to talk with the nurse, and understand [sic] what they had done, what drugs they'd given. (Patient's husband 12)  
Despite noting improvement in the bedside handover process, patients felt that nurses did not have a comprehensive understanding of medical diagnoses, leading to unclear explanations to patients. They perceived communication gaps between nurses and doctors, making it difficult for nurses to respond to patient queries effectively. As a result, nurses advised patients to ask doctors directly for more accurate information. This lack of coordination between nurses and doctors left patients feeling frustrated.  
_In all honesty, I think... it was really a case that the staff really didn't know anything about it....They said, if you want anything, you have to talk to the Dr [name] who... who also works at a different hospital [hospital name], and so he would not be able to get there until maybe every other day....So, there was a real issue with getting information from the nurses...it was quite frustrating for me--is just lack of information...they couldn't add anything, any value to. (Patient 3)_
## 3 Results and Discussion
### Durability Analyses of Different Mixtures  
Results have shown that among all different specimens, except macro-textures, the weakest abrasion resistance belongs to the mixture containing the most common sand, namely natural calcareous sand, the low angularity of which causes the weakest mortar strength. However, as the total aggregate hardness and sand angularity increase with a decrease in the calcareous sand and an increase in the siliceous sand, the sand-to-cement  
Figure 14: Abrasion resistance in form of average mass loss and MTD of brooming macro-textures versus different mix proportions.  
Figure 13: MTD in abrasive seeding macro-textures versus different mix proportions.  
paste adhesion increases resulting in an increase in the abrasion resistance. Therefore, the mixing proportion is very important to construct a durable RCCP surface.  
Considering the price of the natural and manufactured sands and approximately similar abrasion resistance of RCC specimens containing them, using natural calcareous sand can be more appropriate than the manufactured one to achieve an optimal mixing proportion when dealing with the stamping macro-texture. Moreover, since the compressive and abrasion resistance of concrete made with natural and manufactured silica sand highly differ, using the latter is more justified to have a durable RCCP surface when dealing with the brooming macro-texture. However, a mixture of both (either manufactured or natural) can benefit the RCCP (optimize the price and durability) because their prices are highly different due to the higher hardness of the silica sand and more crusher depreciation.
## 2 Mathematical Modeling
### Sliding Mode Controller Design
#### 2.1.3 Control Law Design  
The first-order sliding mode control input consists of two components, which are the nonlinear component \(u_{dis}\) which makes the system states to reach the sliding manifold and a linear component \(u_{eq}\) which enforces the motion and thereby the performance of the system on the sliding manifold. Whenever the system is in the sliding phase, the linear control will force the error variables to the origin and hence the system states to the desired values. Thus, the total control input is given as,  
\[u=u_{dis}+u_{eq}. \tag{9}\]  
Then, the non-linear component of (9) could be designed as,  
\[u_{dis}=\rho\operatorname{sgn}(s), \tag{10}\]  
where \(\rho>0\). We know that during the sliding phase motion \(s=\dot{s}=0\). Hence, the state \(\dot{s}=0\) yields (11) and the equivalent control input \(u_{eq}\) could be computed during this condition as,  
\[\left(\lambda-\frac{1}{\tau}\right)e_{3}-\frac{1}{\tau}u_{eq}=0, \tag{11}\]  
then by rearranging (11), the \(u_{eq}\) is determined as,  
\[u_{eq}=(\tau\lambda-1)e_{3}, \tag{12}\]  
the signum function is described as,\[\text{sgn}(s)=\begin{cases}1&s>0,\\ 0&s=0,\\ -1&s<0.\end{cases} \tag{13}\]  
**Remark 1**.: _The equivalent control (12) is the control input applied to the system (1) after the reaching phase ends, that is, when \(s=0\), to ensure that the system trajectory stays on the sliding surface thereafter. It is worth noticing that this control input is not the actual control that is applied to the system as soon as the sliding surface is reached._