esa-sceva/satcom-chunk-collection huggingface dataset:
# Evaluation of Satellite Imagery for Monitoring Pacific Walruses at a Large Coastal Haulout
## 3 Results

Table 1: Summary of sample sizes, clear-view revisit rates, and observer variations in detecting and delineating walrus aggregations using different types of satellite imagery. Image sample sizes are provided for the total number of archived images, number with a clear view of the study area, and number with walruses detected. Revisit intervals were calculated using only clear-view images, and one per day for PlanetScope. Sample sizes for the average CV-RMSE, average overlap, and regression slope were the number of images with detected walruses pooled across years. All linear regression slopes were statistically significant (P < 0.0001) except for Landsat-8 (P > 0.05). values adhere to the 1:1 reference line displayed in Figure 4, and by the regression slopes presented in Table 1. Lower-resolution imagery types (Landsat and Sentinel-1 EW) had the greatest spatial disparity among observer delineations of aggregations. In fact, some Landsat images produced complete or near-complete disparity in the locations (or even presence) of walruses, and overall had the lowest spatial correspondence among observers. Although the Sentinel-1 EW images had coarser resolution (40 m), observers were unanimous in identifying images with walruses and had slightly better spatial agreement than Landsat in delineating the aggregations. Among the moderate resolution image types (PlanetScope, Sentinel-2, Sentinel-1 IW, and TerraSAR-X stripmap), the spatial agreement among observers was markedly better, with regression slopes ranging between 0.68-0.78. As expected, observers attained the highest levels of 3-way spatial agreement when delineating walrus aggregations with the \(\sim\)1-m-resolution TerraSAR-X staring spotlight, which resulted in an intersection:union slope of 0.85, and with DigitalGlobe, which had an average observer overlap of 0.85 for the one clear view image we obtained with walruses present (Table 1).
# A Novel Localization Technique Using Luminous Flux
###### Abstract  
As global navigation satellite system (GNNS) signals are unable to enter indoor spaces, substitute methods such as indoor localization-based visible light communication (VLC) are gaining the attention of researchers. In this paper, the systematic investigation of a VLC channel is performed for both direct and indirect line of sight (LoS) by utilizing the impulse response of indoor optical wireless channels. In order to examine the localization scenario, two light-emitting diode (LED) grid patterns are used. The received signal strength (RSS) is observed based on the positional dilution of precision (PDoP), a subset of the dilution of precision (DoP) used in global navigation satellite system (GNSS) positioning. In total, \(31\times 31\) possible positional tags are set for a given PDoP configuration. The values for positional error in terms of root mean square error (RMSE) and the sum of squared errors (SSE) are taken into consideration. The performance of the proposed approach is validated by simulation results according to the selected indoor space. The results show that the position accuracy enhanced is at short range by 24% by utilizing the PDoP metric. As confirmation, the modeled accuracy is compared with perceived accuracy results. This study determines the application and design of future optical wireless systems specifically for indoor localization.  
positional dilution of precision (PDoP); localization; indoor positioning; received signal strength (RSS); visible light communication +
Footnote †: journal: Applied Sciences
# YOLO-RRL: A Lightweight Algorithm for PCB Surface Defect Detection
## 2 Algorithm Description
### YOLO-RRL Model  
The YOLOv8 network model represents a more advanced target detection algorithm. It has been developed based on several improvements in previous generations and exhibits advantages in terms of speed, accuracy, and multitasking support. However, in specific applications, there are still slight shortcomings, such as slower inference, inaccurate positioning, and higher requirements for hardware resources. In particular, when confronted with PCB surface defects with small target sizes, issues such as missed detection and target loss frequently arise. Consequently, this paper proposes the YOLO-RRL model for real-time detection of small target defects in industrial applications for PCB surface defect detection. The design objectives of the YOLO-RRL model are twofold: first, to enhance the model's efficiency in resource-constrained environments, and second, to augment the model's capacity to process complex backgrounds. Although the model has been optimized and validated primarily for the detection of surface defects on printed circuit boards, the architectural design and improvement methods are equally applicable to other domains where efficient target detection is required. To make the YOLO-RRL model applicable to other problems, corresponding datasets must be collected and labeled for training and validation in new application areas. The model structure diagram of YOLO-RRL is shown in Figure 1. The specific improvements are as follows:  
1. In the backbone network component, the downsampling module is replaced with the SRFD module, which is employed to process shallow feature maps, and the DRFD module, which is used to process deep feature maps. The two modules in question optimize the representation capability of shallow and deep features according to their different application phases. This ensures the integrity of the information and features robustness in different phases of the downsampling process.
2. In the Neck network component, RepGFPN is employed to supplant the entirety of the feature fusion section while substituting the up-sampling module within it with the Dysample module, thereby yielding a novel feature fusion network (RepGDFPN)as a supplementary Neck layer. The network's multi-scale feature fusion and computationally efficient nature result in high performance and flexibility in object detection tasks. The RepGDFPN network is capable of efficiently handling targets at different scales through the use of multiple up-sampling and feature fusion operations while maintaining high computational efficiency.
3. In the detection head component, LADH-Head is employed for the replacement. This approach reduces the requirement for hardware resources for the model and also has better detection performance.
# Analysis of Influencing Characteristics of Biochars for Ammonium Adsorption
## 2 Materials and Methods  
### Literature Study and Data Selection  
A literature study was performed using Google Scholar and the keywords biochar, nitrogen, ammonium, and adsorption. Articles with clearly reported experimental adsorption capacities that were published from 2013-2022 were used for data collection of different physical and chemical biochar characteristics. In addition, 54 independent research articles were found that had experimentally tested biochar for ammonium adsorption from aqueous solutions. The data from these studies were compared using expectation maximization implemented in Python for data imputation and scikit-learn for principal component analysis and GraphPad Prism to discover trends and relationships between various parameters and the adsorption capacity. All data were fact-checked by calculating the theoretical maximum ammonium adsorption (as defined below) and comparing that value with the reported actual ammonium adsorbed. In some cases, the reported ammonium adsorption was higher than the theoretical maximum; these cases were excluded from analysis.  
\[\text{Theoretical max }(\text{mgNH}_{4})=[\text{NH}_{4}]\text{ in solution }(\text{mg}/\text{L})\cdot\text{volume solution }(\text{L})\]  
As an additional calculation of efficiency, a \"percent of maximum adsorption capacity\" was included. This was calculated by comparing the actual adsorption capacity (experimentally determined) with the theoretical maximum adsorption capacity that was calculated from the fact check above.  
Twenty articles had to be excluded from analysis due to missing information that prevented fact checking or conflicting information reported within the study. For example, the study by [PERSON], [PERSON], and [PERSON] [13] did not include the volume of ammonium solution and grams of biochar used in their experiments, so the theoretical maximum could not be calculated and compared with the reported adsorption capacity. Others such as [PERSON] et al. [14] were removed because they did not report any physical or chemical characteristics of the biochar and therefore did not have enough information to be included in the analysis. A few studies like the one by [PERSON] et al. [15] reported an adsorption capacity that was higher than the theoretical maximum that was calculated using the equation above; therefore, it was not included in this analysis. The inconsistency of analysis provided by the various research studies required pairing down of the data into subsets and thus not all the influencing factors could be compared at one time. Thirty-four articles containing experimental data for ammonium adsorption onto biochar were used for analysis [12; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 42; 43; 44; 45; 46; 47; 48; 49].
# Application of the Improved Entry and Exit Method in Slope Reliability Analysis
## 3 Limit Equilibrium Method  
### Entry and Exit Method  
The critical slip surface is determined by analyzing a certain number of trial slip surfaces, and the one with the minimum safety factor is selected as the key slip surface for the slope. The number of the trial slip surfaces has a significant effect on the calculation accuracy. The entry and exit approach generates a circular slip surface based on three parameters: entry point, exit point, and tangent line (Figure 1). By dividing the entry range \(L_{1}\) into \(n_{1}\) points, the exit range \(L_{2}\) into \(n_{2}\) points, and the vertical distance range between the line A and B into \(n_{3}\) points, \(n_{1}\times n_{2}\times n_{3}\) trial slip surfaces is generated.
# Enabling Heterogeneous IoT Networks over 5G Networks with Ultra-Dense Deployment--Using MEC/SDN
## 3 IoT/5G System Structure
### Radio Access Network (RAN)
#### 3.1.1 Heterogeneous IoT Networks
The proposed offloading algorithm controls data offloading between IoT devices and I-MEC servers in a way that achieves higher energy efficiency and thus prolongs the lifetime of IoT devices. This comes with the announced 3 GPP requirements of IoT as a use case of 5G [6]. The proposed offloading algorithm for IoT networks is presented in Section 4.1.
## 4 The Concept Alignment Example Setup and Modeling
### CAE-ATG Control Events and Interconnection Model
#### 4.3.1 District CS Block  
The district communicates with the fire station to signal the presence of a fire and with the firefighting machines. The CS communicates using two interaction points. Port \(pFS\) allows the interaction with the fire station block; port _ffm_ allows events to be received from the firefighting machines. The details of the exchanged events are summarized in Table 1.  
The presence of a fire was modeled using a specific event (_heOnFire_) modeling both the presence of a fire and the occurrence of an accident causing it. From a modeling point of view, it is an \"external\" event, and it is not associated with any source block (it represents the \"random\" occurrence of the emergency accident, and it can be seen as an \"uncontrolled input\" of the CS). The other events (_evOnFire_ and _evEst_) are exchanged as part of the control algorithm of the fire event: once the fire has been detected, the district sends _evOnFire_ to the fire station to signal it and if the SoS control is effective, it receives an _evEst_ event in a finite amount of time.
# Gaze-Dependent Image Re-Ranking Technique for Enhancing Content-Based Image Retrieval
## 4 Experiment
### Comparison with Re-Ranking Methods  
In this subcategory, we perform an empirical analysis to assess the effectiveness of the proposed method compared with the conventional re-ranking method. Note that the proposed method uses a unique interactive re-ranking method, which converts coordinate-based gaze trace data into semantic information represented in a textual format using image captions. This method distinguishes itself from the conventional interactive re-ranking methods. Considering the above situation, it can be challenging to directly compare our proposed and conventional methods, as reported in [58]. To compare our proposed and existing methods, we evaluate our method against methods presented in [10; 45; 46], which can be assessed under the same conditions. Conventional techniques that obtain relevant feedback from users concerning the highest-ranked images are employed for the evaluation. Initially, we computed the initial retrieval based on the conventional CMIR model, CLIP [23]. Subsequently, we re-ordered the retrieval results using both the proposed method and the conventional re-ranking methods. Finally, we quantitatively compared the re-ranking results. Note that we utilized the hyper-parameters of the conventional interactive re-ranking methods that maximize the average retrieval efficacy.  
Tables 3 and 4 illustrate the experimental results. In the BL column of Tables 3 and 4, the retrieval efficacy of the conventional CMIR approaches is presented. These tables show that the proposed method demonstrates superior performance over the conventional re-ranking methods in terms of retrieval effectiveness. Note that the conventional methods cannot significantly improve the BL retrieval performance. These results are likely due to the failure to determine the inherent query intention inside the query images. In contrast to the conventional re-ranking methods, our method uses gaze information feedback to facilitate re-ranking that accurately reflects user preferences. Based on these results, we could confirm the effectiveness of our method.  
Figure 5: Examples of the original image and its corresponding gaze trace. In (**a**–**d**), the color of the dots in the gaze trace, from light to dark, represents the fixation order. The generated gaze-dependent caption is shown under the image.
# Internet of Vehicles for Sustainable Smart Cities: Opportunities, Issues, and Challenges
## 6 Models of Communication in the Internet of Vehicles
### Vehicle-to-Roadside (V2R)  
Communication refers to the capability of vehicles to interact with road infrastructure, whether it is traffic signs, signals, or ITS equipment. The role of V2R communication in improving road safety and traffic management is very high. These systems are critical to our connected and autonomous vehicle future and toward more efficient, safer, and smarter cities. V2R communication systems can be deployed along roads to mitigate passenger vehicle crashes [78]. A random linear network coding-based message dissemination algorithm at the intersection of the roads was presented for disseminating a novel basic safety message [79]. A data access scheme for V2R communication [80], where the importance of maintaining data integrity is essential to running V2R systems, especially in safety-critical applications. In [81], the data streaming optimization on V2R communication links is carried out through a hierarchical optimization framework considering some important factors such as application-specific requirements, transit service provider, cost considerations, and wireless network service operator profitability. This system-wide approach results in efficient and balanced resource usage in V2R communication systems.
## 4 Discussion
### An Interdisciplinary Redefinition of PRO  
Considering the three definitions by FDA, ISOQOL, and ViBIS, the identified purposes of PRO, and the complexity of the challenges scrutinized in the discussion, it seems appropriate to introduce an alternative definition of PRO. The definition incorporates former aspects of PROs pertaining to research and drug testing while adding more recent clinical practice enabling facets, such as the digitalization of PROs and an alteration regarding who might act as a respondent. Thus, a PRO is defined as a: _validated questionnaire; developed_ in collaboration between patients, clinicians, and other pertinent stakeholders; _systematically_ applied; _mediated_ digitally or paper-based; _completed_ directly by the patient, with assistance or by a qualified proxy; composed of generic, disease-specific, condition-specific or preference-based _measures_; consisting of _content_ pertaining to the patient's physical and mental health condition, functioning, symptoms, well-being or health-related Quality of life (HRQoL); providing objective and/or subjective outcomes, and individual and/or population _data_.  
Essentially, this definition portrays PRO as a multidimensional and interdisciplinary concept; hence, in this version, PRO is a holistic term consisting of several elements regarding specific types of questionnaires, applications, mediations, measures, content, data, and outcomes. Thus, the above interpretation of PRO consists of psychometric measures and/or economic measures and social constructs based on stakeholder perspectives, mediated by a specific technological setup. Therefore, the particular weight on the different aspects shaping a PRO determines its utility and functionality as part of clinical practice.  
The broadness of the definition is required to ensure the bridging between purposes of PRO and the conceptualization of PRO. As a result, this version of PRO underscores its interdisciplinarycharacter, which in combination with the presented purposes above, offers stakeholders on various levels a more nuanced understanding and approach to PRO; potentially, enhancing future healthcare policies and management initiatives based on PRO.  
Regarding limitations, PRO is described in a general manner, meaning that nuances and contextual differences across disease areas and organizational levels are absent. Furthermore, the empirical materials the article is based on does not cover all literature on PRO; hence, some purposes might be missing. Lastly, since the article has a broad scope it limits how profound every theme can be analyszd and elaborated upon; therefore, we encourage future studies to examine issues concerning PRO's different purposes, with a particular focus on the issues emphasized in the discussion section.
## 4 Conclusions and Discussion  
In this study, a MILP model was proposed for sizing a PV and battery hybrid system for a grid connected smart home. Compared to the other existing studies in the area, the harmonic load situation was taken into account in this study and the optimum size of PV and battery was determined for this situation. It should be underlined once again that the study was realized under real power, current, voltage, and harmonics of smart home appliances in Yildiz Technical University, Istanbul, Turkey. Several case studies based on real measurements for the hybrid system and the loads were conducted to assess the impacts of the proposed methodology. The appliance level harmonic components were  
Figure 15: The decomposition of injected power to the grid with PV and battery for sample summer case.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Situations** & **Income Value** & **Outcome Value** & **Value of Total Profit of Hybrid System** \\ \hline Without Harmonic & $1320.501 & $1155.049 & $165.4518 \\ Included Harmonic & $1338.379 & $1171.741 & $166.6377 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Comparison of impacts of harmonic and non-harmonic loads in terms of cost.  
considered to have a bottom-up approach for the cumulative impacts of non-linear loads based harmonic components.  
The impacts of harmonic were found to be at lower levels for an assessment based on just a single household. However, the increase of the number of households and especially consideration of different end-user types such as commercial and industrial with high levels of non-linear loads will show far more clearly the impacts of harmonic components on sizing purposes. Herein, this study can be a starting point for the relevant literature to consider harmonic components within such studies and the smart home-based residential case can here be assumed just as an example for more dominant industrial and commercial load-based sizing studies.  
Therefore, in addition to the proposed work, the consideration of different end-user types, the consideration of harmonic filtering benefit and cost, and the load shifting possibility via an energy management system can be listed as possible future directions of the study both for the Authors of this work and other researchers in the area.  
[PERSON] and [PERSON] mainly contributed by realizing the relevant implementations regarding the formulization and experimental data gathering, and wrote the main parts of the paper. [PERSON] and [PERSON] provided the main idea, and coordinated the overall study. [PERSON] contributed by overall technical suggestions through the research steps and also contributed to the writing of the final research paper.  
[PERSON] acknowledges the support by FEDER funds through COMPETE 2020 and by Portuguese funds through FCT, under POCI-01-0145-FEDER-029803 (02/SAICT/2017).  
The authors declare no conflict of interest.