esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Experiment and Methodology  
### Experiment Details  
The first experiment, an offshore atmospheric optical turbulence in-situ measurement experiment, was implemented from 17 November to 24 December in 2017 in the south of Hainan Island. A field campaign of balloon-borne radiosondes equipped with micro-thermometers and GPS was conducted by the Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences. All the flights were released during the early morning at 7:40 or late evening at 19:40. At the same time, the turbulence strength near the ground was obtained [14; 15]. A comprehensive description of micro-thermometer and its specificationsare given in [16; 17; 18; 19]. During the experiment, the micro-thermometer was installed on a meteorological tower with an altitude of 130 m above sea level, which faced the South China Sea. Furthermore, an ultrasonic anemometer was installed at a distance of 1 m. The turbulence strength derived from two instruments was compared and verified to ensure the validity of the experimental data. The replacement cycle of the temperature sensing foil wires is about 3 days to ensure its sensitivity.  
The open ocean experiment on measurement of atmospheric turbulence aboard ships was developed from October to November in 2020 in the southern part of the South China Sea. During the experiment, the micro-thermometer for near-surface turbulence measurement was always working. In order to reduce the influence from the ship to the instrument, the micro-thermometer extended about 3 m out of the ship. To obtain vertical profile characteristics of optical turbulence over the open ocean, balloon-borne radiosondes equipped with micro-thermometers and GPS were also launched on the ship boat. Typical sunny weather was selected to analyze the optical turbulence strength characters on the open ocean. According to [PERSON]'s freezing hypothesis, the air around the instrument can be regarded as stationary when the shaking amplitude of the ship is relatively small and the speed is relatively slow. The error of the turbulence strength measured by the micro-thermometer is small at this situation. In addition, in order to reduce the influence of salt aerosols on the platinum wires, we controlled the time period for replacing the platinum wires at about 3 days. Less aerosol accumulation makes the measured value more accurate. Similarly, an ultrasonic anemometer was installed at a distance of 1 m to ensure the validity of the experimental data. The photographs of balloon-borne micro-thermometer and experimental scenario picture of micro-thermometer are shown in Figure 1. The red point in the figure is the release position of our balloon-borne radiosondes.
## 3 Result and Discussion
### Detection of New Red Spiked in a Sports Drink Using the MIHs as a Substrate  
**The MIHs were further applied to detect New Red spiked in a sports drink (Gatorade, orange flavored).** As shown in Table 2, the recoveries of samples were found to be in the range of 91.0% to 97.1% and the values of RSD were between 1.8% and 7.7%. The good recovery and RSD indicated that the positively charged Au NPs-embedded MIHs were suitable for the detection of New Red in real samples. As the data collection time for a single SERS measurement is 10 s, the total detection time for a real sample would be less than 2.5 h even when the incubation (2 h) and centrifugation (10 min) pretreatments are included.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Water Sample** & **Spiked (M)** & **Found (M)** & **Recovery (\%)** & **RSD (\%)** \\ \hline
1 & \(1.64\times 10^{-6}\) & \(1.41\pm 0.11\times 10^{-6}\) & \(86.3\pm 6.7\) & 7.7 \\
2 & \(1.64\times 10^{-5}\) & \(1.65\pm 0.72\times 10^{-5}\) & \(100.6\pm 4.4\) & 4.4 \\
3 & \(8.18\times 10^{-5}\) & \(8.05\pm 0.15\times 10^{-5}\) & \(98.0\pm 2.3\) & 2.3 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Percentage recoveries and relative standard deviation (RSD) of the detection of New Red spiked in water samples (mean \(\pm\) SD, N = 3).  
Figure 6: SERS spectra of New Red using the MIH substrate incubated with aqueous solutions of New Red at concentrations of \(1.64\times 10^{-4}\) M (**a**), \(8.18\times 10^{-5}\) M (**b**), \(1.64\times 10^{-5}\) M (**c**), \(1.64\times 10^{-6}\) M (**d**), and \(1.64\times 10^{-7}\) M (**e**); (Inset: Linear correlation of the logarithmic peak intensity at 1572 cm\({}^{-1}\) versus the logarithmic concentrations of New Red).  
The general detection parameters reported in the literature for the determination of New Red are outlined in Table 3. Obviously, the linear range of current method is comparable with other reported methods, and the LOD of current method is better than that of HPLC-UV and HPLC-MS/MS.
# A Review of Performance, Energy and Privacy of Intrusion Detection Systems for IoT
## 5 Privacy Implications of Intrusion Detection Systems
### Analysis  
In this section, we analyze the privacy implications of IoT intrusion detection system for two important features, the data type used for collaboration, and the system architecture.  
Firstly, the system architecture of the detection system determines how data is transferred by the entities in the detection systems. Standalone detection system installed on the user device (e.g., IoT device) or installed at the edge router (entry point router to smart home or the corporate network) operate locally by recording data from the single source, only use data from the single source, therefore, does not have high performance accuracy. The collaborative system, however, operates in two modes i.e., the centralized architecture [14; 43; 55], and the distributed architecture [47; 48; 56]. In the centralized setup, it is envisaged to protect the privacy and integrity of the data provided to it. However, it may not be ideal as the attacker has to compromise only one device to breach the privacy of all collaborators. Furthermore, the centralized system introduces the challenge of single point of failure, which may inhibit efficient collaboration in case of failure.  
The transfer of data to other parties or centralized system has a risk of privacy. In this setting, the collaborating device can operate in four settings: (1) transfer all raw data to the centralized system or other devices that process all the data for meaningful decision. This setting does not have any privacy assurance as data is exposed at other entity whilst also increasing computational workload, (2) transfer processed data for instance exchanging traffic statistics of a host or IP address, however, it still carries privacy threat but without requiring significant additional resources, and (3) the encrypted exchange of data. This setting assures privacy-preservation but requires extensive computation and communication overhead for the exchange of encrypted data.  
Overall, privacy is an important feature which should be guaranteed by intrusion detection system especially within a collaborative system. However, our analysis of the existing literature reveals that the research community has not given much attention to privacy preserving collaboration among the IoT domains or IoT devices. This may be due to resource-constrained nature of IoT devices which limits alert information and cryptographic processing of data due to computational overheads.
# Conflict Resolution in Mechatronic Collaborative Design Using Category Theory
## 4 Conflict Resolution Approach Based on Category Theory
### Proposed Methodology  
As aforementioned, CT is used in this paper to provide a formal framework in order to diagnose and handle the conflicts during mechatronic collaborative design process. The mathematical formalism of CT provides a formal conflict detection and resolution through using the functor concept. All categories defined in this formalism satisfy the formal definitions of CT mentioned beforehand. Moreover, using this mathematical theory collaboration traceability is ensured for reuse perspectives. Our methodology is composed of seven main steps. The flowchart of the proposed approach is presented in Figure 6.  
Figure 6: Flowchart of the conflict resolution approach based on category theory.  
2.1 Step 1: Creating a Common Representational Formalism (P\({}_{\text{m}}\)CG) Based on CT for Parameters Extracted from Expert Models (EMs)  
According to the model-driven architecture (MDA) introduced by the object management group (OMG) [41], a model can be defined as a reality representation and an abstraction of meaningful and relevant things to the stakeholders, described using well-defined languages [6]. Each model contains a variety of knowledge relative to specific expert models. The knowledge defines how different elements are related to each other. Thus, a model can be considered as a set of elements and relations.  
For this reason, it is natural to consider models as graphs. Hence, instead of working directly on the heterogeneous model languages, a unifying formalism is required. These graphs have a formal meaning in the context of CT and highlight all the intuitions coming from the practice. As a first step of our methodology, a formal as well as comprehensive framework is established by means of this mathematical theory. [PERSON] [7] argued that translating all parameters contained in models is not meaningful. Hence, only crucial parameters will be considered in the conflict resolution problem. These parameters are called crucial since their contribution in reaching the project objectives is considered important [42]. To extract knowledge, a close exchange between the project manager and all the engineers involved in the design process is recommended. Some approaches to extract crucial knowledge also exist using multi-criteria decision-making methods [43].  
Thus, for each crucial parameter, a parameter categorical graph (P\({}_{\text{m}}\)CG) is created. The idea is to consider parameters as categories, the objects as the different versions of the parameter used by the EMs and the morphisms as the progress of the concerned parameter from an expert model to another one. Each object in the category has an identity morphism illustrating the natural representation of internal evolution of parameter value. At the end of this step, a set of categories P\({}_{\text{m}}\)CG are obtained where \(m\) represents the number of the crucial parameters involved in the collaborative design.
## 1 Introduction  
Magnetomotive optical coherence tomography (MM-OCT) is a promising imaging method for noninvasive three-dimensional (3D) tracking of magnetically labeled cells in target tissues or organs [1; 2; 3]. In this situation, selected cells are labeled with magnetic micro- or nanoparticles as dynamic contrast agents, which are excited into motion by a modulated external magnetic field. By analysis of OCT signal alterations, this motion can be detected and visualized for enhanced contrast of labeled cells.  
In conventional MM-OCT, the external magnetic field is generated by a solenoid close to the sample. Ideally, magnetomotion is characterized by particle displacement towards the solenoid when the current is switched on, and return of the particle to its initial position when the current is switched off. Hence, besides the magnetic force, also the restoring force of the elastic tissue environment is essential for the retrieval of appropriate magnetomotive signals. To expand MM-OCT to applications and environments where no elastic restoring force is present, such as in liquids, dual-coil configurations were introduced, in which the particles are attracted alternately by a primary and an opposite secondary coil on a common axis [4]. Such a setup would also be convenient for cell imaging, since cells are characterized by viscoelastic properties rather than a true elastic behavior [5]. However, because of the limited space between the two solenoids, this method is restricted to small samples only. Therefore, we introduce an alternative method called rotational magnetomotive (rMM)-OCT which uses two magnets on the same side of the sample but with two different axes. This off-axis configuration allows the generation of modulated longitudinal and transverse magnetic fields, which cause magnetomotion by the alignment and rotation of anisotropic magnetic particles in the sample volume.  
For our experiments, we used a multimodal imaging system presented recently by our group [6]. This system allows MM-OCT imaging in combination with light microscopy and laser speckle reflectometry for structural and motion analysis of single cells. For the implementation of rMM-OCT, we added a small permanent magnet to the existing setup to generate the transverse magnetic field. After analysis of magnetic field components and particle behavior, we provide proof-of-principle evidence for rMM-OCT imaging of single mesenchymal stem cells (MSCs) embedded in agar scaffolds and demonstrate the magnetomotive signal enhancement compared to previous pulsed MM-OCT. Finally, we use our method to image ARPE-19 cells [7], a human retinal pigment epithelium (RPE) cell line, in order to demonstrate the potential of rMM-OCT to track therapeutically relevant cell types, such as RPE cells transplanted into the retina [8; 9].
# An Empirical Recommendation Framework to Support Location-Based Services +
## 2 Related Work and Comparative Analysis
### Other RS Systems  
[PERSON] et al. (2019) proposed an RS for online shopping. Decision tree and association rules are merged into this system to generate recommendations. Association rules give the user's pattern and the user's interest is identified using a decision tree. Combining these two results the final interests can be found. [PERSON] et al. (2019) introduced a Grid structure to divide objects into different groups and performed further analysis. Because of the finite number of grids, the use of a grid-based structure gives fast processing results. [PERSON] et al. (2019) introduced a framework of a system based on knowledge. Here they used the Fuzzy Cognitive Maps (FCMs) method to generate recommendations. [PERSON] et al. (2019) analyses on heterogeneous data to identify suggestions. This proposed approach integrated lexical, syntax, and semantic analysis to understand user preferences. [PERSON] et al. (2019) proposed a machine learning technique for recommending restaurants with personal interests. Here the NLP algorithm is used to evaluate the positivity of previous responses. The PITF-BPR algorithm is used to model these records. Baidu map cloud service is used by [PERSON] et al. (2019) to implement another restaurant recommending system. [PERSON] et al. (2019) proposed a friend recommendation system based on three collaborative frameworks. They considered check-in location, common friends as the parameter for this work. Considering two parameters: price and ratings, [PERSON] et al. (2019) introduced a grid-based algorithm to recommend restaurants. [PERSON] et al. (2019) proposed a hybrid model for movie recommendation. They combined the _K-means_ algorithm with the generic algorithm for partitioning the user data. Finally, a principal component analysis (PCA) is employed to carry out the recommendations.  
In this paper, we present an empirical framework to support location-based services. The main contributions of this paper can be summarized as follows.  
* Generating users interest profile.
* Adapting grid-structure to reduce processing time.
* Recommending the best possible places for a group of users.
## 5 Experimental Results
### Memory Analysis
#### 5.2.4 Comparison  
Table 10 shows the comparison of the number of states in the automaton of the AC algorithm and the PA. The number of states in the automaton of the PA is considerably fewer than that in the AC automaton. Each transition between states in the AC automaton results in processing only a single character. That is, a single state represents a single character transition. Therefore, the number of states created for a pattern is equal to the character length of the pattern. However, the fact that a state can represent more than one byte in the automaton of the PA causes the number of states to be much fewer than that in the automaton of the AC. As a result, the memory requirement for storing the states is less in the proposed automaton. Table 11 compares the memory space required for AC, WM, and the PA in the pattern-matching process. As shown in the table, the memory space required for the PA is much less than that for the other two algorithms.
## 3 Results and Discussion
### Tool Wear and Hole Quality  
Figures 8-10 show the worn cutting edges of the three type diamond coated tools at the end of the drilling tests. It suggests that all the diamond coated tools encounter abrasive wear. The worn surface area is becoming smaller from MCD to NCD/MCD surfaces. In Figure 8, the WC-Co substrates are obvious because of the film delamination. It is noted that the delamination area of MCD coated tools with condition I is smaller than that of condition II, due to the intense impact between tool and workpiece in higher speed spindle on the rough surface of MCD. As to NCD coated tools shown in  
Figure 6: Force value versus the number of drilled holes under condition I.  
Figure 7: Force value versus the number of drilled holes under condition II.  
Figure 9, the delamination is more severe under condition I than under condition II, which suggests the opposite phenomenon in contrast to MCD coated tools. This is attributed to smoother surfaces enduring less friction under high spindle speed. The MCD/NCD coated tools present a similar situation to NCD coated tools, but with a smaller worn area and less film delamination in Figure 10, suggesting the best performance during the CFRP drilling test. In the MCD structure, the film cracks tend to propagate through the columnar particles, leading to a decrease in toughness and adhesion. As to NCD coating, the continuous structure would relieve the crack propagation, but the hardness of NCD is lower than that of MCD. The advantages are integrated in the composite MCD/NCD structure, which leads to the high hardness and prevents crack propagation.  
Hole quality in CFRP drilling consists of output parameters including surface integrity, hole diameter, delamination, and exit burrs of drilled holes. Delamination is classified as exit hole damage which is very critical in structural durability of the composite structures. In this study, hole quality of machined CFRP specimens is evaluated with delamination damage. The delamination factor (Fd) adopted in this study is a factor defined as the ratio of the maximum diameter (Dmax) of the delamination area to the hole nominal diameter (Dnom), as illustrated in \(\mathrm{F_{d}}=\mathrm{D_{max}}/\mathrm{D_{nom}}\). The morphologies of the 50 th hole exit under \(n=4000\) rpm are shown in Figure 11. The values of Fd for the holes drilled by MCD, NCD, and MCD/NCD coated tools are 1.14, 1.09 and 1.03. It indicates that the composite coating coated tool could achieve high quality.  
Figure 8: Worn morphology of cutting edge for MCD coated tools. (**a**) \(n=4000\) rpm, \(f=0.004\) mm/r; (**b**) \(n=6000\) rpm, \(f=0.008\) mm/r.  
Figure 9: Worn morphology of cutting edge for NCD coated tools. (**a**) \(n=4000\) rpm, \(f=0.004\) mm/r; (**b**) \(n=6000\) rpm, \(f=0.008\) mm/r.
###### Abstract  
Through the feedback of the rotor speed and/or the grid frequency, an energy storage system (ESS) can effectively suppress the electromechanical oscillation of a power system. This paper proposes a novel control strategy and controller parameter design method for ESSs to achieve the desired performance of oscillation suppression, including smaller frequency and rate of change of frequency (ROCOF) deviation than their threshold values. Firstly, a dynamic model of the electromechanical time scale of a synchronous generator dominated power system with ESS was established. Then, based on the dynamic model and the electric torque analysis method, the mechanism of an ESS with the feedback signal of the rotor speed to suppress the electromechanical oscillation was investigated. Finally, the controller parameter design method for the ESS was developed to achieve the desired performance of oscillation suppression. With the help of the well-designed ESS, the electromechanical oscillation of a synchronous generator dominated power system can be effectively suppressed in shorter transient response times, and the grid frequency deviation and the ROCOF can be limited to below their threshold values. The simulation results also verify the effectiveness of the proposed control strategy and the controller parameter design method.  
energy storage system (ESS); electromechanical oscillation; controller design; inertia and damping; frequency deviation; rate of change of frequency (ROCOF) +
Footnote †: journal: Applied Sciences
###### Abstract  
Position and orientation deviations (PODs), being affected by surface deviations, occur after parts are assembled, which directly affects the performance of mechanical products. Moreover, mechanical parts are generally assembled with multiple constraint planes, and the generated PODs are influenced by the type of positioning. Therefore, the PODs of multiple planes should be computed in the design stage according to the predicted surface deviations, to control the product performance. However, even though the POD computation of multiple planes has been researched, the effects of surface deviations and multiple types of positioning cannot be considered simultaneously. To address this problem, this study proposes a point-by-point-contact-based approach. The six-point positioning principle is employed to determine the possible number of contact points on each mating plane. The surface deviations are modeled from the perspective of manufacturing errors. Furthermore, the contact points on each mating plane are determined successively using both the strategies of progressively approaching position and of the orientation and recursion of contact points. As a result, the PODs are acquired. The feasibility and usefulness of the proposed approach are verified through a case study. Herein, effects of surface deviations and multiple types of positioning on PODs are unified as contact point variations. Consequently, this approach is expected to assist with accurately controlling the POD influence on the performance of mechanical products in the design stage.  
multiple planes; positioning surface deviations; search algorithm; position and orientation +
Footnote †: journal: Applied Sciences