esa-sceva/satcom-chunk-collection huggingface dataset:
# Dynamic SDN Controller Load Balancing
## 1 Introduction  
In a software defined network (SDN) architecture [1], the logical separation between control plane and data plane, in the architecture and functional behavior of network nodes, is dissociated, allowing for centralization of all the logic related to control plane procedures in a so-called SDN Controller. In turn, this allows for simplified network nodes designed and streamlined for data plane performance. Such an architecture enables developers to devise new algorithms to be collocated at the SDN controller, which are able to manage the network and change its functionality [2, 3]. Even though only one controller may handle the traffic for a small network [4], this is not realistic when we deal with large network at the internet scale since each controller has limited processing power, therefore multiple controllers are required to respond to all requests on large networks [5, 6, 7]. One approach to achieve this goal is to use multiple same instantiations of a single controller [8], where each instantiation ofthe SDN controller does basically the same work as the others, each switch being linked to one SDN controller. Handling multiple controllers gave rise to some important questions, namely: where to place the controllers and how to match each control to a switch. These questions are not only relevant during the network deployment based on static's information [9; 10] but should also be considered regularly due to the network dynamic nature [11]. In this paper we dealt with the matching problem aforementioned. We proposed a novel multi-tier architecture for SDN control plane which can adapt itself to dynamic traffic load and therefore provide a dynamic load balancing.  
The rest of this paper is organized as follows. In Section 2 we present the state of the art in dealing with load balancing at the control plane level in SDN. Then in Section 3 we present the updated DCF architecture used to develop our clustering algorithm. In Section 4, the problem is formulated and its hardness explained. The two-phase Dynamic Controllers Clustering (DCC) algorithm, with the running time analysis and optimality analysis, is provided in Section 5. Simulations results are discussed in Section 6. Finally, our conclusions are provided in Section 7.
# High-Throughput Line Buffer Microarchitecture for Arbitrary Sized Streaming Image Processing
## 3 Method
### Buffer Architecture in D-SWIM
#### 3.2.2 Line-Rolling Behavior of Line Buffers  
The buffer in D-SWIM stores and loads the successive image lines with the line-rolling mechanism. To demonstrate the line-rolling clearly, we show an example with \(H=3\), \(N_{blk}=4\) in Figure 6. At the beginning, the LB0-LB2 are stored in the Line0-Line2, respectively. When the buffer receives the incoming Line3, the input block is stored in LB0 and replaces the old pixels of Line0 which is no longer needed. With this _line-rolling_ mechanism, the successive image lines are stored in all LBs in a cyclic manner.  
Figure 5: (**a**) shows LB write behavior with conventional BRAM usage. (**b**) shows LB write behavior with the byte-wise write enable signal using BRAM primitive instantiation.  
Meanwhile, the buffer outputs a 2D window including pixels from \(H\) image lines, and the blocks in the window are spatially aligned to the input block. As Figure 6 shows, the first two blocks of the output window are loaded from the LBs, while the last one is directly sourced from the input block. Because the output blocks are aligned in the vertical direction, the 2D windows are continuous in the horizontal direction. Thus, the output 2D windows cover all the pixels required by an arbitrary 2D pattern with a height of \(H\).
# Comparing Sentinel-2 and Landsat 8 for Burn Severity Mapping in Western North America
## 4 Discussion
### The Paired Scene Approach  
In addition to being a well-established and widely used method for burn severity mapping, testing the paired scene approach allowed us to evaluate the impact of atmospheric and terrain corrections to Sentinel imagery. Atmospheric correction is demonstrated to increase NDVI with both Landsat and Sentinel due to an increase in reflectivity in the near-infrared spectrum and decrease in the visible range of the electromagnetic spectrum [82], and also affects shortwave infrared light reflectance [83], which is used in NBR indices. Additionally, use of atmospherically corrected imagery is particularly important when comparing burn severity across fires in different regions or years, as we carried out in this study, due to differences in atmospheric conditions [84].  
The Sen2 Cor post-processing algorithm [68], which applies atmospheric and terrain corrections to Sentinel TOA imagery to create BOA scenes, improved burn severity correlations with CBI data for all indices, with a particularly large boost for RdNBR (Table 5). This was notable since the uncorrected Sentinel TOA imagery still performed similarly, or even slightly better, than the corrected Landsat imagery. Given that image compositing with Sentinel TOA imagery improved performance for all NBR-derived indices comparedto the paired scene approach, it is likely that applying the image compositing approach to the Sentinel BOA catalog will result in further improvements. This is possible for fires occurring in 2020 or later, which we were unfortunately unable to test in the current analysis because our most recent field data were collected from 2019 fires.  
Even though we attempted to minimize differences between the acquisition dates of the scene pairs acquired by Landsat and Sentinel, for some fires, the chosen pre-fire Sentinel image was more than a month, and in some cases more than a year, apart from the Landsat counterpart (Table S1). This was unavoidable and potentially impacted the resulting burn severity estimates, but in all cases we made sure to match the post-fire scene's season as closely as possible to the acquisition time of the pre-fire Sentinel image, as seasonal differences between paired scenes are shown to have a large effect on burn severity estimates [85].
## 1 Introduction
However, these advantages require choosing a suitable extraction system and effectively considering all kinds of factors affecting the extraction separation in order to fully come into play. Extraction, washing and reverse extraction are three complementary processes in extraction and separation [11; 12; 13; 14]. The deep research of scandium by Chinese scientists began with V-Ti magnetite in Panzhihua area of China. The value of scandium accounts for about 47% of Panzhihua V-Ti magnetite. The economic value of scandium is more than four hundred million USD, ranking first in the economic value of all elements of Panzhihua V-Ti magnetite. Because the grade of Panzhihua V-Ti magnetite is not high, it produces a large amount of tailings, which not only occupy much arable land, but also pollute the environment. There are rare scandium-containing minerals, making it difficult to separate and extract scandium. Consequently, scandium and its compounds become rather expensive. Scandium in V-Ti magnetite is mainly enriched in the tailings of titanium separation by beneficiation process, so it is necessary to extract scandium from the tailings of titanium separation. The tailings of V-Ti magnetite are pretreated by magnetic separation gravity separation electro separation process to enrich scandium to obtain scandium concentrate. To obtain scandium products with a high purity and recovery rate, it is necessary to combine multiple methods to improve the extraction process, to find more materials that can recover scandium--as well as improve the recovery and extraction methods of scandium, which will be of great significance to the effective use of the source [15; 16; 17; 18]. Scandium oxide (Sc\({}_{2}\)O\({}_{3}\)) is the most common scandium compounds. Scandium oxide from high temperature burning is not soluble in dilute acid, but soluble in boiling concentrated nitric acid. Scandium chloride (ScCl\({}_{3}\)) is an important raw material for the further preparation of scandium metal and Al-Sc alloy [19; 20; 21; 22]. To date, the key point of preparing ScCl\({}_{3}\) is how to reduce the hydrolysis rate of scandium chloride in ScCl\({}_{3}\). For this reason, a new one-step rapid heating process is proposed to prepare high-purity anhydrous ScCl\({}_{3}\) with the low-purity Sc\({}_{2}\)O\({}_{3}\) (purity, 81.16%), along with the appropriate technological conditions. The high-purity anhydrous ScCl\({}_{3}\) will deeded as the important scandium-bearing raw materials for the preparation of Sc-bearing master alloy by aluminum-magnesium thermal reduction.
###### Abstract  
In order to increase transmission capacity, multiplexing schemes in different physical dimensions, including time, frequency, modulation quadrature, polarization, and space, can be employed. In this work, we propose and demonstrate a red color laser-diode (LD) based visible-light-communication (VLC) system using two kinds of digital domain multiplexing schemes, orthogonal-frequency-division-multiplexing (OFDM) and power-domain division-multiplexing (PowDM). The two digital domain multiplexed data can achieve data rates of 1.66 Gbit/s and 6.41 Gbit/s, respectively, providing a total data rate of 8.07 Gbit/s, fulfilling the pre-forward error correction (pre-FEC) bit-error-rate (BER) limit. The measured signal-to-noise ratios (SNRs) are 10.96 dB and 14.45 dB, respectively. Here, similar to OFDM, the PowDM can enhance the total system capacity by allowing acceptable signal spectra overlapping among different power division signals to maximize the bandwidth utilization. An experiment to verify and evaluate the proposed work is performed. The modulation and demodulation of OFDM and PowDM are discussed. The optimum power levels of the individual signals in the PowDM signal are also analyzed.  
Keywords:optical wireless communication (OWC); visible light communication (VLC); orthogonal frequency division multiplexing (OFDM); laser diode (LD) +
Footnote †: journal: _Photonics_
# A High-Precision Energy-Efficient GPS Time-Sync Method for High-Density Seismic Surveys
## 3 Performance Evaluation and Field Measurement for Validation
### Field Measurement II  
To evaluate the reliability and performance of the proposed time synchronization method by the sensor node for seismic exploration, a field survey was conducted on the Chaoyang campus of Jilin University. At the survey location, 17 sensor nodes are arranged in a row with 2.5 m pitch, as shown in Figure 15a. Then we did a hammer test at 3 m from the 9 th node. The exploration test took about one hour. Other parameters of the GEIWSR-III are set in Table 2. The test results are shown in Figure 15b. All instruments have good consistency and synchronization, which fully meet the requirements of the time synchronization of all nodes in high-density seismic array surveys.  
Figure 14: Field measurement with the sensor nodes in a pile (**a**) the sensor nodes are deployed in one field experiment and (**b**) the waveform of the recorded seismic data.
## 11 Applications of the Integration of Blockchain and Cloud Computing
### Smart Manufacturing
#### 11.4.3 Blockchain as a Driver of Digital Business Transformation  
\"Blockchain\" is an open-source distributed database that uses cutting-edge encryption. One of the most widely used blockchain applications is Bitcoin, which utilizes an open ledger [47]. Everyone can observe what is going on with an open-source platform, since anyone can update the underlying code. There are no middlemen to validate or to settle transactions, making it a real peer-to-peer (P2P) system. Various structured data may be stored in the system, including who paid whom, what money belongs to whom, or what light source provided the electricity ([PERSON] and [PERSON] 2017). Although recent studies have shown security vulnerabilities on various platforms, blockchain is generally unhackable, making it a trustworthy platform. For example, the cost of confirming transaction data may be reduced thanks to the blockchain, and intermediaries can be eliminated. Blockchain transactions function by broadcasting every block in the system to all parties, each receiving an exact copy of the transaction. An irreversible and transparent transaction record is created when all parties in the network agree on the transaction, such as sending money from one party to another [36]. In the financial service industry, blockchain is widely used to conduct financial transactions, also known as cryptocurrencies. Currently, cryptocurrencies are among the most prominent software systems. The first transaction occurs during the creation of the first block, or genesis block. The first block's hash is forwarded to the miner, who uses it to generate a hash for the next block. Similarly, the third block creates a hash that includes the first two blocks, etc. It is possible to trace the chain of blocks in a blockchain back to the genesis block. In the current healthcare system, interoperability issues exist and healthcare blockchains can address that. It can be used as a standard for securely exchanging electronic health records (EHR) between healthcare entities, medical researchers, etc. Users can work with patient data without exposing their privacy by using the system. Using taxonomies in blockchain technology can help analyze blockchains and design and test software architectures. Using their taxonomy, they cover all the main architectural features of blockchains and the impact of various decisions. This taxonomy aims to assist in evaluating the performance and quality attributes of blockchain-based systems. The various other applications of blockchain in cloud computing are given with scientific evidence in Table 4 below.
# Spatio-Temporal Variations of Ecosystem Water Use Efficiency and Its Drivers in Southwest China
## 3 Results
### Dominant Factors Influencing Variations in Ecosystem WUE  
The spatial distribution patterns of the dominant factors influencing WUE variation are shown in Figure 5, as indicated by the maximum %IncMSE value among these factors (temperature, precipitation, and EVI) at each pixel. Specifically, EVI was the largest contributor to the spatio-temporal variations in WUE, accounting for 59.59% of the entire study area, especially western and northeastern Guizhou and west-central Guangxi. The regions most influenced by temperature and precipitation accounted for 18.23% and 22.18%, respectively, of the total study area, showing only a small difference. Temperature was the most influential factor influencing variation in WUE in southern Yunnan and southwestern Guizhou, while precipitation was the most influential factor mainly in southeastern Guizhou and northeastern Guangxi, with the other meteorological factors sporadically distributed in southern Yunnan and southern Guangxi. Combined with the landform areas (Figure 1c), the non- karst landform areas were mostly dominated by meteorological factors, such as temperature and precipitation, while the karst areas were mostly dominated by EVI.  
To further investigate how EVI is the dominate factor influencing changes to ecosystem WUE, the interannual rate of EVI variation was divided into regions exhibiting significant increases and decreases (\(p<0.05\)). The areas with significant increases were almost always the same as the areas with EVI as the most dominate factor influencing WUE variation, accounting for 65.83% of the total study area, with 1.56% demonstrating a significant decrease, which were scattered throughout northern Yunnan (Figure 6a). The mean value of ecosystem WUE was high in areas exhibiting a significant increase in EVI and showed an increasing trend (Figure 6b). The mean ecosystem WUE was low in areas with significant degradation in EVI and exhibited a decreasing trend, demonstrating that the increase in EVI in the study area is an important factor for an increase in ecosystem WUE. The EVI indicators characterizing vegetation coverage were relatively largely increased in the study area, thereby maintaining the overall increase in ecosystem WUE throughout the total study area (Figure 3a).  
Figure 5: Spatial distribution of dominant factors influencing variations in ecosystem WUE.
### Organisation  
The article's structure presents the reader with the basics of the technologies and their practical applications. Initially, the problem is outlined, and why sound, although often overlooked, can be a valuable carrier of information in intelligent systems. The following sections describe the key technologies used for acquiring and analysing acoustic data, including sensors, machine learning algorithms, and data processing architectures. Particular attention is paid to real-world examples of acoustic systems applications, from medicine and industry to public safety. At the end of the article, current challenges, possible development directions, and the future of sound monitoring in the context of AI and IoT are discussed.
## 4 Analysis of Delays within a Router
### Quantifying Parameters  
The experiments provide results which were distributed over a large range of values. An average value of the range was calculated in order to provide a single value associated with each test.  
Results show that some parameters in the equation have a greater significance than others. The average delay for each Dr is shown in Table 2 which indicates that there are significant differences in packet processing time depending on the OS version used.  
By using a router with a basic OS rather than an advanced OS it can be seen that standard routing is faster by around 15%. This is even without configuring any extra services on the advanced OS which it is expected would further increase the latency. When ACLs are configured then for a basic OS the average delay is increased by around 80% for a standard ACL and 110% for an extended ACL. However, by replacing the basic OS with an advanced OS and configuring a standard ACL saving of around 12% can be made and for an extended ACL 6%.
# Detecting and Localizing Dents on Vehicle Bodies Using Region-Based Convolutional Neural Network
## 4 Conclusions  
The present study proposed and applied a region-based convolutional neural network (R-CNN) to detect and localize dents on the surface of a vehicle body. An adaptive genetic algorithm (AGA) explored the optimal combination of hyper-parameters for the R-CNN by an evolutionary process to achieve the best classification accuracy. The R-CNN established a classification network, which classified an input image into either normal or abnormal (dent). In addition, the R-CNN localized the estimated location of a dent using the heat-map. The proposed method was able to classify normal and abnormal patches with an accuracy of 98% and its MAE was 13.7 pixels, which indicated very small discrepancy between the actual and estimated dent locations. It is expected that the R-CNN proposed in this study could help detect and localize dents on a vehicle exterior during vehicle manufacturing and for assembly companies.  
Although the findings of this study revealed such promising results, there is still room for improvement in the future studies. Three further works were suggested for better practical applicability of the R-CNN model. First, this study used images of a vehicle fender to train the R-CNN model, and thus the model was specialized for detecting defects on the fender; however, the model might be applicable to other parts of a vehicle body. To validate the applicability of the R-CNN model developed in this study, further studies are needed to evaluate the classification performance of the method for other parts of a vehicle body. Second, this study demonstrated that the hybrid model could classify an image as normal or abnormal with great accuracy. Therefore, the model could be useful in the development of a real-time inspection system, which could record consecutively images of a vehicle body and detect defects. Lastly, this study used artificial defects on a vehicle body; thus, the future study can be suggested to develop and evaluate R-CNN models for detecting normal defects naturally damaged during the vehicle manufacturing as well as assembly process.  
Conceptualization, S.H.P., M.C., and J.P.; methodology, S.H.P. and A.T.; software, S.H.P., M.C., and J.P.; validation, J.C. and K.J.; writing--original draft preparation, S.H.P., M.C., J.C., and J.P.; writing--review and editing, A.T. and K.J.; supervision, J.C. and K.J.; project administration, K.J.; funding acquisition, K.J. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT; NRF-2019R1A2C4070310, NRF-2018R1C1B5045699).  
Figure 8: Examples of the actual and predicted dents.
# Personalization of the 3D-Printed Upper Limb Exoskeleton Design--Mechanical and IT Aspects
## 5 Discussion
### Sensor Technology and Data Acquisition  
Sensors and artificial intelligence-based solutions are increasingly being used to collect data during activities of daily living, which can be useful in planning and monitoring rehabilitation and controlling adherence to home therapy programs [63].  
In a study by [PERSON] et al., immediate improvements in range of motion (ROM) and upper limb function were seen in 50% of hand exoskeleton users, with the most challenging task being the gripping and releasing of various objects [64]. In a subsequent study by [PERSON] et al. [65], nine subjects (69.23%) could not perform functional tasks without assistance and only one showed improvement in task performance with the exoskeleton [65]. Thus, the use of an exoskeleton alone does not guarantee improvement and must be combined with a thoughtful, targeted rehabilitation plan. Another study addressed the use of a hand exoskeleton in a group of post-stroke patients with flexor hypertonia and finger extensor weakness [66]. Such a deficit has a direct negative impact on the opening movement of the hand, and therefore, the correct execution of the grip. The HandSOME (Hand Spring Operated Movement Enhancer) hand exoskeleton supports the patient's hand opening by stretching the finger joints and compensating for flexor hypertonia. Design, after calibration, was subjected to functional and usability testing with eight post-stroke patients with the above-mentioned hand deficits, which showed an increase in the patients' range of movement and functional abilities [66]. Sometimes it is necessary to develop a dedicated compact flexible actuator that, however, requires separate validation at the prototype stage [67].  
The proposed solution, through the use of cameras, is ready to be used as a data source for digital models, virtual twins and virtual reality (VR). Research by [PERSON] et al. [9] has shown that VR can support patient engagement in therapy, improve the friendliness of the robotic environment, simulate real-life manipulation tasks and modify them in real time, thus increasing the effectiveness of exercises and shaping their support and requirements. Unfortunately, the solution has only been tested on one userso far [68].  
Brain-computer interfaces (BCIs) involving the control of hand movement through motor imagery have proven effective, but there are few prototypes due to the high price. One such solution is the Hand Exoskeleton for Rehabilitation Objectives (HERO) combining 3D printing (including 3D-printed actuators that convert the torque of DC motors into a linear force transmitted through Bowden strings) and textiles. Two-dimensional (2D) tracking software and correlation analysis were performed to assess ergonomics. With an exoskeleton weight of 102 g, a classification accuracy of motion intention read from the electroencephalogram of 91.5% was achieved [69]. Such a solution is more difficult in signal analysis [70; 71] but more future-proof and ultimately more effective and closer to natural limb control solutions [72; 73].