esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Conclusions and Future Perspectives  
The continuous technical progress has made it an overwhelming trend to integrate smart devices with emerging ICT techniques to reshape the industrial applications. M2M-enabled collaborative automation is a central technical issue to maximise machine efficiency and production flexibility. Motivated by the challenges in integrating data and information level techniques with low-level mechanical machines, this article discusses technical solutions toward machine interoperability in production line scale. Considering the specificities of industrial machines and the requirements, a reference system architecture and the CoM2M messaging mechanism are presented focusing on the connectivity, messaging, and understanding between machines. Its application in the PicknPack food packaging system has demonstrated the feasibility and its flexibility. The practice of the PicknPack system is a valuable reference solution for practitioners to innovate different industrial applications.  
Along with the introduction of new technologies and concepts in manufacturing industry, such as IoT, wireless sensor networks, service-oriented technology, and big data, a lot of advanced manufacturing modes or national strategies have been put forward, including Industry 4.0, Flexible Manufacturing System (FMS), smart products, Made in China 2025, Internet Plus Manufacturing, and Cloud Manufacturing. Two technical issues will become the focal points of these new concepts of manufacturing: (1) the manufacturing efficiency based on data interaction and machine collaborations, and; (2) intelligent product and production process optimisation based on manufacturing data. The CoM2M presented in this paper allows real-time data interaction and collaborative automation between machines in order to promote the manufacturing efficiency of industrial networks with the solutions for machine network system modelling, flexible presence and discovery, ubiquitous M2M messaging, and machine understanding. The open framework also allows the system to implement high-level intelligence obtained from big data for production efficiency and product variability. With the progress of the computerisation of machine parts in the manufacturing industry, industrial networks will become more complicated, which may require the building of a connection with product designers, source providers, sales, markets, and customers, M2M messaging will become a challenge but also a driving force of future industrial IoT applications.  
The work presented in this paper has been supported by the European Commission through PicknPack project (ID: 311987). The authors would like to thank all project partners for their contributions, especially researchers from Wageningen UR and KU Leuven for their support in machine communications and software integration. [PERSON] and [PERSON] conceived the design and development of the system according to the progress of the project; [PERSON] performed the implementation and experiments, and wrote the paper; [PERSON] and [PERSON] provided supervisions and supports for the research work. The authors declare no conflict of interest.
## 3 Results
### Querying TribAIn  
Originating from the research questions introduced in Section 3.1, formal queries were applied in the knowledge base using SPARQL 1.1 query language [34; 35], showing how the knowledge linked with tribAIn can be represented. Since the research questions (1), (3), and (4) are quite similar and allocated with the general use case (1) from Section 2.2, the following query (Box 1) is exemplarily suggested for answering research question (1).  
Figure 12: Formal definition of the tribosystem studied in the component test.  
Figure 13: Linking CAD data to a device.  
The SELECT expression queries four variables as expected output, which are further filtered through the WHERE expression. The filter searches for the variables under the condition of a tribological reference method with steel/steel contact, sliding kinematics, and a tribosystem without any interfacial medium (MINUS) as well as related frictional behavior as a result with the target variable humidity, which was compared with a reference humidity (Figure 14).  
The output table shows the section from the publication annotated as _FrictionReduction_ and the compared humidity values for this investigation (Figure 14). In comparison, in questions (3) and (4), the MINUS expression was replaced by another WHERE condition, which adds MXene as solid lubricant to the body of the queried reference method. Furthermore, in question (4), the target variable humidity was replaced by pressure.  
Besides SELECT queries, research question (2) is suggested as the following ASK query (Box 2), which can only retrieve YES or NO stating whether a possible solution to this query exists or not:  
Figure 14: Graphical example of the formulated query filter and example output for research question (1).  
As the query asks for a reference method, which resulted in a friction reduction under the condition that MXene is used as a solid lubricant, the query returns YES as, for instance, the resulting frictional behavior in Figure 10 was annotated as _FrictionReduction_. Furthermore, the ASK query could also be used for coverage queries as intended in use case (2).
## 2 Materials and Methods
### OCT and Data Acquisition  
A spectral-domain PS-OCT system (TEL220 PSC2, Thorlabs, Lubeck, Germany) was utilized for imaging the brain samples. The setup used a multiplexed superluminescent diode in the near infrared (central wavelength 1300 nm, bandwidth 170 nm) and achieved a theoretical axial resolution of 5.5 \(\upmu\)m in air. The theoretical lateral resolution was 7 \(\upmu\)m (at the focal plane), using a commercial scanning lens with a focal length of 18 mm (OCT-LK2, Thorlabs, Lubeck, Germany). The focus was positioned at the tissue surface for imaging. For the acquisition, a lateral (x,y) field of view of 500 pixels \(\times\) 500 pixels in a cortical region of the sample was imaged, corresponding to 500 \(\upmu\)m \(\times\) 500 \(\upmu\)m. The imaging depth range was 3.5 mm in air. The A-scan rate was 76 kHz and a sensitivity of 109 dB was measured. OCT images displaying backscattered intensity and retardation were computed from the raw spectral data. All volumes were saved as image stacks for further processing.
## 3 Results and Discussion
### Evaluation of the Analytical Method  
The applicability of DLLME combined with HS-SPME/GC-MS in the analysis of flavor enhancers (maltol and ethyl maltol) in seafood was evaluated based on linear range, sensitivity, stability, and accuracy. The standard curves of maltol and ethyl maltol were obtained by adding maltol standard (0.25-25 \(\upmu\)g/g) and ethyl maltol standard (0.05-40 \(\upmu\)g/g) into dried squid substrate. As shown in Table 1, the method had an excellent linear relationship, and the correlation coefficients (R2) of the calibration curves for maltol and ethyl maltol were greater than 0.995. In this study, the limit of detection (LOD) values of maltol and ethyl maltol were 5.0 \(\upmu\)g/kg and 2.5 \(\upmu\)g/kg, respectively. In addition, the limit of quantification (LOQ) values were 15 \(\upmu\)g/kg and 5.0 \(\upmu\)g/kg, respectively. As compared with the previously reported methods of solid-phase extraction and dispersed liquid-liquid microextraction (DSPE-DLLME), ionic liquid (IL), and solid-phase extraction (SPE), the LOD and LOQ of the developed method were relatively low (Table 2). Obviously, DLLME coupled with HS-SPME was sensitive for determining maltol and ethyl maltol in complex matrix samples.  
The relative standard deviation (RSD) was detected to evaluate the stability and repeatability of the DLLME/HS-SPME pretreatment method. Intraday precision and interday precision were determined by adding a 5.0 \(\upmu\)g/g mixed standard solution of maltol and ethyl maltol to dried squid samples. As shown in Table 1, the intraday accuracy ranged from 2.8 to 5.7% and the interday accuracy ranged from 3.5 to 4.3% for the DLLME/HS-SPME method. The results indicated that the developed method was stable and reliable.  
The recovery rate of this method was evaluated by adding three different concentrations of maltol and ethyl maltol standard solutions to dried squid samples. The recovery results showed that the pretreatment of instant dried squid by the DLLME/HS-SPME method did not affect the accuracy of GC-MS detection of flavor substances. As shown in Table 3, the recovery rate of maltol in matrix samples ranged from 89.0 to 118.6%, and that of ethyl maltol in matrix samples ranged from 96.0 to 112.1%. The results suggested the developed method was accurated for determining maltol and ethyl maltol in complex matrix samples.
# HPoC: A Lightweight Blockchain Consensus Design for the IoT
## 3 Problem and Solution Analysis
### Proof of Security and Tamper Resistance of Blockchain  
A blockchain is a data structure made up of a series of blocks that are linked together by a cryptographic hashing algorithm. Each block's header contains a hash, which may be thought of as a collection of all the information from the previous block. Because hashing is collision-resistant and one-directional, it allows users to check the consistency of blocks right away. However, the blockchain is not impeccably secure; by changing the hash in the block header sequentially from one block to the next, a new chain with an entirely different chain can be created, a phenomenon known as forking in blockchain systems. The PoW is based on obtaining a random number that matches the criterion, and only nodes that have paid a high computational cost may do so. This makes rebuilding a new chain prohibitively expensive, thus preventing malicious tampering. While the process of locating that random number provides the blockchain with tamper resistance and security, it also drastically slows down block-generating efficiency. It might be claimed that PoW is a two-edged sword that provides security while reducing efficiency, and that a method is needed to offset this impact while still contributing to the block's security.  
To summarize, developing a lightweight blockchain in the IoT edge-computing scenario necessitates not only a holistic approach and a novel design from the standpoint of consensus, but also a unique ledger layout and data structure. We explore the four issues raised above in this section and provide remedies, such as constructing a double-leader parallel election model to reduce the election stage's impact on the block-generating stage. An election algorithm based on PoC combined with VRF is designed to ensure the randomness of the election. In addition, a hierarchical structure consists of minute blocks, ten-minute blocks, and day blocks with which asynchronous PoW is used, which can reduce the storage pressure on non-leader nodes and separate the PoW computation process from the block-generating process to ensure the blockchain's security and tamper evidence while maintaining a high block-generating speed. The next section will discuss the specific consensus process and algorithm design, as well as the corresponding data structure and chain architecture.  
The proposed method has the following advantages: (1) low price and ultra-low power consumption--POC only needs a computer hard disk to mine, so the cost of mining input is lower; (2) the efusal to monopolize, with stable income--POC is relatively fair and naturally anti-monopoly; (3) strong risk resistance--POC is easier to sell or be reused.
## 4 System Testing and Performance
### System Testing Considerations  
The tests that were carried out followed several parameters to guarantee their usefulness.  
1. Flight duration: the UAV flights were scheduled to last at least five minutes to obtain significant information about the drone's flying capabilities, bearing in mind that some height and distance should be manageable as well. They were measured in ranges of hundreds of meters, so they guaranteed that the drone could fly significant distances to collect information.
2. Manoeuvring: the open-source drone built by the team members performed all possible movements in three dimensions (yaw, pitch, roll) to ensure that it had full mobility when in the air.
3. Data collection: the data that was collected was required to be significant for the purposes of the presented system. Therefore, it was required that it contained the parameters deemed as mandatory according to the non-functional requirements set in the previous section.  
Furthermore, there were several external and internal elements associated with the tests that were performed. These were as follows:  
1. Unfavourable weather conditions: the measurements to be taken relied on the built UAV being able to freely fly in a space as open as possible. Unfortunately, when the equipment associated with the MDAS was finally ready to be installed in the drone, there were severely unfavourable weather conditions. Consequently, UAV flights had to be planned and performed with extreme care not to damage the equipment that was being used. Despite these inconveniences, the authors of the paper were able to obtain accurate information about power levels from third and fourth generation mobile networks and map them with the coordinates that reflected where the UAV was when the measures were taken.
2. Information formatting data: as previously explained, the information collected is directly obtained from the Network Cell Info application for Android terminals. The data are obtained in Comma-Separated Values (CSV) format, and come with a plethora of parameters (the coordinates, altitude and power level of the strongest signal that is being measured) of different usability for the purpose of the proposal. The most useful data had to be picked from all the parameters to have it represented in a suitable manner.
3. Program coding: the GUI was programmed using MATLAB (Matrix Laboratory) as the programming language, due to its facilities to operate with matrix-formatted data. MATLAB imposed several syntax rules that must be followed, which, in the end, posed no issue at all.
## 2 Study Area and Data Sources  
### Study Area  
The study area, located in southern Sichuan Province, China, includes four counties (Ebian Yi Autonomous County, Emeishan City, Ganluo County, and Jinkouhe District), covering approximately 1667 km\({}^{2}\) (Figure 1). The area is located in the transition zone, with the Tibet Plateau in the west, the Yunnan Plateau in the south, and the Sichuan Basin in the northeast. The Dadu River from the Tibet Plateau crosses this area and flows to the northwest, separating the border minorities from the inner majorities. Mount Emei, in the northeast, is a famous national scenic spot. The geologic structures are complex, and the elevation in this region ranges from 363 m in the northeast basin to 4242 m in the south mountain.  
Figure 1: Location map and landslide inventory of study area.  
The region experiences a subtropical humid monsoon climate, with rainfall concentrated in the summer months, particularly in July and August. Due to the significant topographic variation, the annual precipitation varies greatly, ranging from approximately 470 mm in the valleys to 1922 mm at higher elevations, such as Mount Emei. The mountains exert a screening action on humid air flows with consequent condensation, which results in heavy rainy events.  
A total of 589 landslides are recorded in the official document. Many large-scale landslides occurred in this area and caused significant losses and casualties. Among them, the Liziyiida gully debris flow is well known. It killed over 240 people and disrupted the central railway from Chengdu to Kunming on 9 July 1981, nearly the biggest catastrophe in Chinese railway history [25].  
We have conducted multiple studies in the research area with abundant landslide data. A total of 12 conditioning factors for LSP were selected in this study, including geological, topographical, and vegetation coverage data.
# Concept Justification of Future 3 DPVS and Novel Approach towards its Conceptual Development
## 3 Conceptual Design Approach for 3 DPVS  
After utilizing the LSE to justify the 3 DPVS concept, this part will introduce the conceptual design process for 3 DPVS. This design approach is considered as novel for several reasons. First, previous 3D scaffold designs were largely based on an experimental approach; for example, it is often the case that biological engineers use a \"trial and error\" method to modify previously established scaffold model or product to achieve the new one required by a definite research scenario. This is applicable for scaffold design where only quantitative changes are made. Other design approaches lie in establishing 3D models by CAD tools to make suitable geometries or mechanical properties. For both of the two ways previously used, these could not be effective for the conceptual design of 3 DPVS, chiefly due to the fact 3 DPVS is a totally new concept different from a traditional 3D static or passive scaffold.  
Considering the aforementioned issues, authors in this research attempt to introduce the engineering design process (EDP) into the scaffold design, as well as adapting the design process for tailored 3 DPVS conceptual development. In the following sections, the general EDP will be introduced firstly, then the conceptual design process of 3 DPVS. This 3 DPVS conceptual design is proposed to contain three stages, namely design initiation, concept generation and concept evaluation.
###### Abstract  
Conventional relative kinematic positioning is difficult to be applied in the polar region of Earth since there is a very sparse distribution of reference stations, while precise point positioning (PPP), using data of a stand-alone receiver, is recognized as a promising tool for obtaining reliable and accurate trajectories of moving platforms. However, PPP and its integer ambiguity fixing performance could be much degraded by satellite orbits and clocks of poor quality, such as those of the geostationary Earth orbit (GEO) satellites of the BeiDou navigation satellite system (BDS), because temporal variation of orbit errors cannot be fully absorbed by ambiguities. To overcome such problems, a network-based processing, referred to as precise orbit positioning (POP), in which the satellite clock offsets are estimated with fixed precise orbits, is implemented in this study. The POP approach is validated in comparison with PPP in terms of integer ambiguity fixing and trajectory accuracy. In a simulation test, multi-GNSS (global navigation satellite system) observations over 14 days from 136 globally distributed MGEX (the multi-GNSS Experiment) receivers are used and four of them on the coast of Antarctica are processed in kinematic mode as moving stations. The results show that POP can improve the ambiguity fixing of all system combinations and significant improvement is found in the solution with BDS, since its large orbit errors are reduced in an integrated adjustment with satellite clock offsets. The four-system GPS+GLONASS+Galileo+BDS (GREC) fixed solution enables the highest 3D position accuracy of about 3.0 cm compared to 4.3 cm of the GPS-only solution. Through a real flight experiment over Antarctica, it is also confirmed that POP ambiguity fixing performs better and thus can considerably speed up (re-)convergence and reduce most of the fluctuations in PPP solutions, since the continuous tracking time is short compared to that in other regions.  
P 2019 11 992 2019 10.3390/rs11080992
## 3 Current Status of the Circuit Component in the MMW Regime
### Recent Works of SoC in MMW Regime
#### CMOS MMW Transceivers
Tuning range of 38 GHz VCO with doubler and 77 GHz VCO shows 69.6-81 GHz and 75.2-79.2 GHz, respectively. Moreover, the PA has a gain of 14.3 dB and P1 dB of 10 dBm with 236 mW power consumption. Furthermore, in [202], the Doppler radar transceiver has a down-conversion gain of 16 dB and an NF of 7-9 dB over an IF bandwidth of 17 GHz. The transmitter output power, as measured at the output of one of the two PAs, varies between \(+\)1 and \(+\)3 dBm over the VCO tuning range of 90.6-93.5 GHz. Regarding 32 nm CMOS technology, a SOI CMOS 210 GHz fully differential transceiver was implemented [166]. The receiver has a sensitivity of \(-\)47 dBm with a noise figure of 12 dB. The transmitter has an EIRP of 5.13 dBm with a 3 dB bandwidth of more than 14 GHz. This chip demonstrates the possibility of advanced CMOS technologies for implementing the transceivers beyond 200 GHz.
## 2 Principles and Algorithms
### Kriging Interpolation  
Kriging interpolation [22] leverages spatial autocorrelation statistics. Its core principle is minimizing the variance of estimation error. The fundamental kriging algorithm, often termed ordinary kriging (OK) interpolation, assumes a spatially constant but unknown mean (i.e., stationary data). The interpolation formula is:  
\[Z(x)=\sum_{i=1}^{N}\lambda_{i}Z(x_{i}) \tag{6}\]  
where \(Z(x)\) represents the predicted value of the point \(x\) to be inserted, \(\lambda_{i}\) denotes the weight coefficient determined by minimizing the variance of the prediction error, and \(Z(x_{i})\) expresses the value of the known point \(X_{i}\).  
The weight \(\lambda_{i}\) coefficients of ordinary kriging satisfy the following constraints:  
\[\sum_{i=1}^{N}\lambda_{i}=1 \tag{7}\]  
The weights are calculated utilizing a semivariance function \(\gamma(h)\) that describes the variation in similarity between known points as distance \(h\) increases:  
\[\gamma(h)=\frac{1}{2N(h)}\sum_{i=1}^{N(h)}\ (Z(x_{i})-Z(x_{i}+h))^{2} \tag{8}\]  
where \(h\) represents the distance between two points, and \(N(h)\) denotes the logarithm of points whose distance is \(h\).  
The semivariogram model is fitted by the semivariogram theory \(\gamma(h)\). The commonly utilized semivariogram models are:  
(1) Spherical:  
\[\gamma(h)=\left\{\begin{array}{ll}0,\ h=0\\ C_{0}+C(\frac{3h}{2a}-\frac{h^{3}}{2a^{3}}),\ 0\leq h\leq a\\ C_{0}+C,\ h>a\end{array}\right. \tag{9}\]  
(2) Exponential:  
\[\gamma(h)=C_{0}+C(1-e^{-\frac{h}{2}}) \tag{10}\](3) Gaussian:  
\[\gamma(h)=C_{0}+C(1-e^{(-\frac{h}{2})^{2}}) \tag{11}\]  
(4) Linear:  
\[\gamma(h)=C_{0}+kh \tag{12}\]  
\(\gamma(h)\) represents a semi-variogram model, \(C_{0}\) denotes the nugget effect, \(C\) expresses the base value, \(a\) depicts the variation.
# Multi-Sensor Fusion for Aerial Robots in Industrial GNSS-Denied Environments
## 3 Results  
### Test Scenario  
The environment used for validating our algorithm is in the CATEC (Advanced Center for Aerospace Technologies) facilities, which contain an indoor multi-vehicle aerial testbed (see Figure 4). This space enables the development and testing of different algorithms applied to multiple aerial platforms. The testbed dimensions are 15 m \(\times\) 15 m \(\times\) 5 m. It has a motion capture system based on 20 Vicon cameras, which allow the control of the full volume through the use of passive markers that are placed on the aerial robot. This system can provide, in real time, the position and attitude of the aerial vehicle with millimeter precision. The sample rate of data acquisition for our experiments was 100 Hz, enough for acquiring a high-quality ground truth for evaluating localization algorithms.  
Figure 4: Vicon camera (**left**) and CATEC indoor testbed (**right**).
# Big Data Collection in Large-Scale Wireless Sensor Networks
## 2 Overview of WSNs
### Topologies of WSNs
#### 2.3.1 Star Topology  
In this communication topology, the network consists of a single station that can send and/or receive messages from a number of remote sensor nodes. Sensor nodes are not allowed to communicate with each other. This topology has the advantages of being easy to deploy, and guaranteeing communication and low latency between remote sensor nodes and the base station [44].