esa-sceva/satcom-chunk-collection huggingface dataset:
# Human Activity Recognition Based on Point Clouds from Millimeter-Wave Radar
## 2 Data Collection Using Frequency Modulated Continuous Wave (FMCW) Radar  
The dataset used in this study was collected using the RETINA-4 SN radar (Smart Radar System, Gyeonggi, Republic of Korea) of the Smart Radar system [22]. The RETINA-4 SN radar is an FMCW and multi-input-multi-output (MIMO) millimeter-wave radar that can obtain \((x,y,z)\) coordinates and \(p\) (power) for each point in a point cloud at a rate of 20 frames per second. The detailed specifications of the radar are listed in Table 1.  
The data collection process was carried out as shown in Figure 1, where the radar was positioned 0.8 m above ground. Data were collected by having a person perform the actions of each class in the center of a 5 m long and 4 m wide area. A total of three volunteers (subjects), two men and one woman, participated in the experiment. Their heights ranged from 163 to 180 cm, and their weights ranged from 58 to 80 kg. The collected dataset was organized into 11 classes based on activities that often occur in daily life. An example of point-cloud data for each class is shown in Figure 2. Frames with fewer than 10 points included in one frame were excluded from the dataset. Table 2 shows details of the dataset, where each class consists of approximately 1000 to 1100 frames, the maximum number of points in a frame is 1280, and there is an average of 343 points per frame across all classes.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Quantity** \\ \hline Start frequency & 77 GHz \\ Stop frequency & 81 GHz \\ Bandwidth & 4 GHz \\ Azimuth angle FoV & 90\({}^{\circ}\) \\ Elevation angle FoV & 90\({}^{\circ}\) \\ Detection range & 12 m \\ Number of transmitter antennas & 12 \\ Number of receiver antennas & 16 \\ Number of frames per second & 20 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Radar specifications.  
Figure 1: Data collection setup.  
Figure 2: Configuration of dataset classes and their corresponding point clouds: (**a**) Stretching; (**b**) Standing; (**c**) Taking medicine; (**d**) Squatting; (**e**) Sitting chair; (**f**) Reading news; (**g**) Sitting floor; (**h**) Picking; (**i**) Crawl; (j) Lying wave hands; (**k**) Lying.
## 2 Related Works  
### LSB Matching Revisited  
Introduced by [PERSON] [10] in 2006, the LSB matching revisited technique represents a significant innovation in steganography, enabling the embedding of messages within monochrome images. By skillfully altering pixel pair values to discretly modify the LSB, this technique ensures hidden messages are effectively embedded without compromising the image's visual fidelity. Its primary advantage lies in concealing information while maintaining the original appearance of the image, significantly reducing detection risks.  
The method encodes covert messages by adjusting the LSBs of pixel values, minimizing perceptual differences between original and modified images. Such precision in pixel alteration is crucial for obscuring the embedded message, thus preserving the image's authenticity.  
Message bits \(m_{i}\) and \(m_{i+1}\) are embedded using consecutive pixel values, \(x_{i}\) and \(x_{i+1}\), with the steganographic image representing these pixels as \(y_{i}\) and \(y_{i+1}\). Converting \(x_{i}\) to \(y_{i}\) involves encoding the message bit into the LSB, allowing it to seamlessly integrate with the pixel's binary structure.  
Central to this technique is the binary function \(f\), outlined in Equation (1), which determines the need for pixel value adjustments to embed the following message accurately:  
\[f(x_{i},\ x_{i+1})=LSB\Big{(}\Big{|}\frac{x_{i}}{2}\Big{|}+x_{i+1}\Big{)} \tag{1}\]  
This function \(f\) guides the embedding process, indicating how pixel pairs \(x_{i}\) and \(x_{i+1}\) are modified to encode the message bits \(m_{i}\) and \(m_{i+1}\). If the LSB of \(x_{i}\) aligns with \(m_{i}\), no modification is made, and \(y_{i}\) remains as \(x_{i}\). Conversely, if \(f\) mandates an adjustment, \(x_{i}\) is incremented or decremented by one to correctly capture the message bit, thus changing \(y_{i}\). Similarly, \(y_{i+1}\)'s value is adjusted based on \(f(x_{i}-1,\ x_{i+1})\) in relation to \(m_{i+1}\).  
[PERSON]'s approach is further validated by its reduction in the average number of pixel adjustments needed for embedding messages. Experiments indicate that this method averages just 0.375 changes per pixel, a notable improvement from the previous standard of 0.500 changes with traditional LSB techniques. This advancement not only confirms the method's high efficacy, but also its concordance with theoretical models. Figure 1 explains the details of this LSB match process.
## 3 Data Integrity Ontology in SPuMoNI
### ALCOA/ALCOA+ Principles  
GxP is an acronym representing \"good practice\", guidelines, covering all regulated fields, as denoted by the use of \"x\", which set quality standards and enforce regulatory requirements in various industries including the pharmaceutical manufacturing industry. Good manufacturing practices (GMP) is a member of the GxP family of guidelines, aiming to ensure that products are safe and meet their intended use. Regarding the pharma regulatory requirements, compliance to the ALCOA Attributable, Legible, Contemporaneous, Original, Accurate, Complete, Consistent, Enduring, and Available principles reside at the core of GMP.  
The _Attributable_ principle involves inspection of whether data are associated with the person responsible for data collection. _Legible_ refers to the requirement that data records must be readable for any use. This involves inspection of whether text data values are in UTF-8 character encoding and include only valid words and if numeric decimal data values have the same format. The _Contemporaneous_ principle checks whether all data items are associated with the date and time of their recording. The _Original_ principle is based on the assumption that when a report is submitted for the first time it is considered as original. Any modifications detected in a subsequent re-submission of the same report result in its characterization as being not original. _Accurate_ involves the examination of whether all data items have values that lie within the acceptable ranges. The _Complete_ principle involves the inspection of whether all mandatory data fields of a report have values and are not empty. _Consistent_ refers to whether data items have starting dates preceding their ending dates. The _Enduring_ principle refers to data record availability for the entire period for which it might be needed, by checking whether it is associated with a date after which it will not be stored. Finally, _Available_ involves the inspection of whether the report has a date associated with it after which it will not be accessible.
## 2 Materials and Methods
### Evaluation of the Sustainability of the Proposed Technology  
Recently, a rapid and suitable method to compare two materials, based on an index, was been introduced [7,34]. This approach is named ESACPE, standing for Evaluation of Sustainability of material substitution using carbon footprint by a simplified approach. This approach was proposed to support industrial transition to CE, by means of a method, based on the use of simplified indicators, for the evaluation of raw materials substitution sustainability.  
An index (SUB-RAW index, see in the following) was introduced as a parameter to quantify the environmental benefices of a raw material substitution. It is evaluated only taking into account two parameters, strictly connected to the environmental performance of the considered materials, that are embodied energy (EE) and CO\({}_{2}\) footprint (CF).  
The materials production from ores and feedstock requires energy, which is defined as \"embodied energy.\" EE accounts for all direct and indirect energies needed for the production of 1 kg of a material [35]. The CO\({}_{2}\) footprint corresponds to the equivalent mass of greenhouse gases (kg CO\({}_{2}\) equivalent), produced and released into the atmosphere due to the production of 1 kg of the material [35].  
Figure 3: X-ray diffraction (XRD) pattern of stabilized fly ash (FA) after 11 months.  
In general, The EE and CF account for the resources and the emissions, respectively, involved in the synthesis of a material.  
These parameters do not take into account functional and economical properties of the considered materials. Indeed, the basic idea of the proposed method is to use a simplified approach to evaluate material substitution. This is the reason the procedure must be simple and accessible to all.  
Eventually after the positive results obtained by the ESCAPE method it would be possible to perform complete Life Cycle Assessment analysis, to globally evaluate the proposed material substitution.  
The SUB-RAW index is defined as:  
\[SUB-RAW\ index=\ \frac{[\log(EE_{mnw})-\log(EE_{sub})+\log(CF_{mw})-\log(CF_{sub} )]}{2}, \tag{2}\]  
where the subscripts _raw_ and _sub_ stand for raw material and new proposed material, respectively.  
The \(EE\) and \(CF\) range from 0.01 to 10\({}^{6}\)-10\({}^{7}\), respectively reported in kg/kg and MJ/kg. Due to the large range of values, a logarithmic scale is often used. All the \(EE\) and \(CF\) parameters are used without their dimension, obtaining a dimensionless numerical value. It corresponds to a mean parameter accounting for environmental pressure and energies of the two materials, that are compared.  
The goal to substitute natural resources with more sustainable materials is obtained when the index results positive. A positive value of this index, even if it is very low, can be a very good result in terms of substitution.  
For example, a SUB-RAW index of about 0, 1, indeed, corresponds to a mean variation of \(EE\) and \(CF\) of about 25%.
# Comparing Augmented Reality-Assisted Assembly Functions--A Case Study on Dougong Structure
## 1 Introduction  
Dougong is one of the most remarkable features of ancient Chinese architecture (see Figure 1) and plays a vital role in the development of traditional buildings in East Asia. It is an architectural design that cushions the ceiling of the structure, and also distributes the weight throughout the building [1]. A Dougong structure consists of a series of pallets placed on top of a column, wooden interior support beams, and external supporting materials. Owing to its complex structure, people usually have difficulty in understanding and learning from two-dimensional (2D) drawings and paper documentation about the construction of the Dougong. More effective methods of knowledge transfer and the presentation of its assembly are still lacking.  
Augmented reality (AR) is a human interfacing technology that has recently become popular in various industrial and business sectors. (Human interfacing technology refers to a software and/or hardware technology with which information is shared with people using sensory stimulus.) AR provides a highly interactive environment in which humans interact with digital contents, objects, and environments in real-time. In addition to gaming and entertainment, AR applications have been successfully deployed in other industries such as commerce, healthcare, education, and manufacturing [2]. Leading global companies such as Apple, Google, and Microsoft consider AR to be one of the most futuristic technologies and have invested significant resources in its technical development.  
Modern companies need to shorten the product's development time in response to ever-increasing economic globalization. Manual assembly/disassembly is still a common task in many industrial sectorsdespite the recent progress of Industry 4.0 technologies. Traditionally, when a product is assembled from components, its assembly instructions, drawings, and operation descriptions are presented in a 2D format or on paper, or both. Such a presentation form fails to precisely demonstrate the spatial relationships among the three-dimensional (3D) components comprising a product, which are critical to its manual assembly. Operators may need extra time or effort to comprehend the presented information, increase the assembly time, and consider the possibility of committing human errors. Computer-aided tools have been developed to facilitate manual assembly since the late 1980s. Most of them utilized computer-aided design (CAD) technologies, which are not necessarily for or accessible to people on the shop floor. Early development of these tools might not have considered their usability. AR applications have the potential of solving such inefficiencies with their highly interactive nature in 3D space.
## 3 System Description  
This study has the following main objectives:  
1. Develop a heuristic design formula to achieve optimum transmitter locations for a square room geometry; hence, optimize the illuminance and \(SNR\) uniformities with a minimum number of transmitters2. Achieve a BER of \(10^{-9}\) (or less) for the OOK-NRZ modulation scheme to ensure an unbroken and reliable communication link with the received \(SNR\) > 15.6 dB in worst-case low-intensity scenarios  
By determining the optimum positions of the LED transmitters for given room dimensions, it would be ensured that the illuminance uniformity is optimized, \(P_{r}\) is evenly distributed, the fluctuations in \(SNR\) are minimum, and the least \(SNR\) value is well above the defined \(SNR\) threshold. To realize these goals and present our results in the next section, this segment covers the description of generalized methodology, system and channel models, proposed LED design layout algorithm, and other related material required to carry out the ray-tracing simulations.
## Appendix B Quasi-Static Method Algorithm  
The following makes reference to an equilibrium equation given above (Equation (10)):  
1. The values of \({}^{n}\mathbf{q}_{\mathbf{D}}\), \({}^{n}\tilde{\mathbf{q}}_{\mathbf{D}}\), \({}^{n}\tilde{\mathbf{q}}_{\mathbf{D}}\), \(\mathbf{f}_{\mathbf{E}\mathbf{D}}(\tau_{n+1})\), \(\mathbf{q}_{\mathbf{i}\mathbf{P}}(\tau_{n+1})\)\(\forall i\), and the contact states' effective stiffness matrices \({}^{n}\mathbf{K}_{\mathbf{i}}\) and \({}^{n}\mathbf{K}_{\mathbf{S}\mathbf{i}}\) are known either from initial conditions or the previous integration step.
2. PREDICTOR: It is assumed that the contact state at \(\tau_{n+1}\) is the same as that of the previous time step, i.e., \[\begin{split}{}^{n+1}\widetilde{\mathbf{K}}_{\mathbf{i}}& =^{n}\mathbf{K}_{\mathbf{i}}\\ {}^{n+1}\widetilde{\mathbf{K}}_{\mathbf{S}\mathbf{i}}& =^{n}\mathbf{K}_{\mathbf{S}\mathbf{i}}.\end{split}\] (A17)
3. It is therefore possible to compute the expression of \({}^{n+1}\widetilde{\mathbf{q}}_{\mathbf{D}}\) using the tentative version of the equilibrium equations at time \(\tau_{n+1  
4. Vector \({}^{n+1}\widetilde{\mathbf{q}}_{\mathbf{D}}\) is transformed into local displacements at the contact \({}^{n+1}\widetilde{\mathbf{q}}_{\mathbf{iD}}^{*}\) using Equation (4). The same is done with the displacements of the platform contact points, thus obtaining \(\mathbf{q}_{\mathbf{iP}}^{*}(\tau_{n}+\Delta\tau)\ \forall i\).
5. The vectors of local displacements at the contacts (of both the platforms and the damper), together with the slider variable \(\mathbf{s}_{\mathrm{i}}\) are fed into a function (similar to the contact element function) that checks whether their values are compatible with the postulated contact condition. In other words, for each \(i\), whether the structure of \({}^{n+1}\widetilde{\mathbf{K}}_{\mathrm{i}}\) and \({}^{n+1}\widetilde{\mathbf{K}}_{\mathrm{Si}}\) is compatible with the values of local platforms and damper displacements is checked (see Table 1).
6. CORRECTOR: If the compatibility is verified, then the equilibrium postulated in Equation (10) is indeed satisfied, and the integration goes to \(\tau_{n+2}\). In this case, all slider variables are updated according to the verified contact condition (\({}^{n+1}\mathbf{s}_{\mathrm{i}}\), to be used at time step \(\tau_{n+2}\)). Otherwise, the structure of all effective contact stiffness matrices is updated according to the indications of the function mentioned at Step 5--see also Table 1: \[\begin{split}{}^{n+1}\mathbf{\hat{K}}_{\mathrm{i}}& =\mathcal{F}\left({}^{n+1}\widetilde{\mathbf{q}}_{\mathbf{iD}}^{* },{}^{n+1}\mathbf{q}_{\mathbf{iP}}^{*},{}^{n}\mathbf{s}_{\mathrm{i}}\right) \\ {}^{n+1}\mathbf{\hat{K}}_{\mathrm{Si}}&=\mathcal{F} _{5}\left({}^{n+1}\widetilde{\mathbf{q}}_{\mathbf{iD}}^{*},{}^{n+1}\mathbf{q} _{\mathbf{iP}}^{*},{}^{n}\mathbf{s}_{\mathrm{i}}\right).\end{split}\] (20) The algorithm is then repeated starting from Step 3.
## 4 Description of the Proposed Topology Construction
### Design Issues of the Proposed Logical Topology
#### 4.5.5 Identifying and Isolating Aberrant Nodes  
Sensor nodes that do not function as specified must be identified and isolated in order to continue the desired operation of the sensor network. An aberrant node may be the result of an attack or may act  
Figure 14: Leader selection time _vs._ network lifetime.  
Figure 15: Leader selection time _vs._ time required.  
maliciously due to unexpected network behaviour. According to [42], an aberrant node is one that is not functioning as specified, and may cease to function as expected for the following reasons:  
1. it has exhausted its power source or is damaged by an attacker,
2. it is dependent upon an intermediate node and is being deliberately blocked because the intermediate node has been compromised,
3. an intermediate node has been compromised and is corrupting the communication by modifying data before forwarding it, or,
4. a node has been compromised and communicates fictitious information to the BS.  
Therefore, the WSN should be maintained by identifying an aberrant node quickly and isolating it from the sensor network. The protocol named SecCOSEN [28] can be used for authentication purposes. This protocol perfectly suits the logical topology, as it was designed for a multiple chain oriented logical topology. Using this protocol, a node can authenticate the node from which it receives data/messages. If a node is not able to authenticate another node in the chain, the former node reports the incident to the chain leader. In addition, a node also maintains a timer for identifying any dead node with the help of timeouts and reports the incident to the leader node.
_applied sciences_  
_Article_  
**Evaluating the Quality of Patient-Specific Deformable Image Registration in Adaptive Radiotherapy Using a Digitally Enhanced Head and Neck Phantom**  
[PERSON] 1,2,*(c), [PERSON] 1, [PERSON] 1, [PERSON] 3, [PERSON] 3, [PERSON] 1(c), [PERSON] 2 and [PERSON] 2(c)  
Medical Physics Unit, Azienda USL-IRCCS di Reggio Emilia, 42122 Reggio Emilia, Italy School of Engineering, Cardiff University, Cardiff CF24 3 AA, UK Radiotherapy Unit, Azienda USL-IRCCS di Reggio Emilia, 42122 Reggio Emilia, Italy Correspondence: [EMAIL_ADDRESS] or [EMAIL_ADDRESS] Tel.: +39-0522295987**  
**Featured Application: This paper presents a deformable image registration-based method for the quality assurance of head and neck adaptive radiotherapy using digitally post-processed anthropomorphic phantom image datasets. One of the main findings of this work is that spatial and dose errors are a function of the magnitude of the deformation and of the gradient of the dose distribution. This emphasizes the importance of performing patient-specific deformable image registration verification and, consequently, the need to develop and make available tools that are for this purpose.**  
Despite the availability of national and international guidelines, an accurate and efficient, patient-specific, deformable image registration (DIR) validation methodology is not yet established, and several groups have found an incompatibility of the various digital phantoms with the commercial systems. To evaluate the quality of the computed tomography (CT) and on-board cone-beam CT (CBCT) DIRs, a novel methodology was developed and tested on 10 head and neck (HN) patients, using CT and CBCT anthropomorphic HN phantom images, digitally reprocessed to include the common organs at risk. Reference DVFs (refDVFs) were generated from the clinical patient CT-CBCT fused images using an independent registration software. The phantom CT images were artificially deformed, using the refDVFs, and registered with the phantom CBCT images, using the clinical registration software, generating a test DVF (testDVF) dataset. The clinical plans were recalculated on the daily patient 'deformed' CTs, and the dose maps transferred to the patient-planning CT, using both the refDVF and testDVF. The spatial and dosimetric errors were quantified and the DIR performance evaluated using an established operative tolerance level. The method showed the ability to quantify the DIR spatial errors and assess their dose impact at the voxel level and could be applied to patient-specific DIR evaluation during adaptive HN radiotherapy in routine practice.  
deformable image registration; multimodal image registration; adaptive radiotherapy; head and neck; verification
## 3 Results  
In total, 64 of the 99 detected chemical compounds were identified in chamomile essential oil (Figure 4, Table 4) and are consistent with the chromatographic profile provided by the manufacturer (Avicenna Oil, Poland) and with the literature data. Bisabolol oxide A was found in the largest amount (39.25%), which is within the specified value in the literature (2-60%), as well as in the chromatographic profile of the manufacturer and the European Pharmacopoeia (PE) (\(\geq\)20%). The next largest amounts were \(\alpha\)-farmesene (19.39%) (in the literature: approx. 8%) and \(\alpha\)-bisabolol (14.87%) (in the literature: 1-60%; Avicenna Oil and PE: 10-65%) [17; 18; 20; 28; 29]. The compound that gives the oil its characteristic blue color, chamazulene, was found in an amount of 2.23%. This is consistent with the literature data, according to which this oil contains from 2 to 25% of chamazulene, while both the manufacturer's specification and the European Pharmacopoeia state its content as equal to or above 1% [17; 18; 20; 28]. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**No.** & **Chemical Compounds** & **Content** & **Content According to Manufacturer’s** & **Content According to European** \\  & & **in EO [\%]** & **Specifications Avicenna Oil [\%]** & **Pharmacopoeia 7 [\%]** \\ \hline
1 & Ethyl 2-methylbutyrate & 0.09 & NA & NA \\
2 & \(\alpha\)-Pinee & 0.01 & NA & NA \\
3 & Propyl & 0.03 & NA & NA \\
4 & \(\beta\)-Fellandren & 0.01 & NA & NA \\
5 & Yomogi alcohol & 0.03 & NA & NA \\
6 & \(\beta\)-Cymene & 0.05 & NA & NA \\
7 & \(\beta\)-Terpineol & 0.02 & NA & NA \\
8 & \(\alpha\)-Pinee & 0.02 & NA & NA \\
9 & \(\beta\)-cis-Ovemene & 0.20 & NA & NA \\
10 & Ketone artemisinin & 0.29 & NA & NA \\
11 & \(\gamma\)-Terpinene & 0.09 & NA & NA \\
12 & Alcohol artemisinin & 0.05 & NA & NA \\
13 & Bornel & 0.01 & NA & NA \\
14 & Eliksen & 0.29 & NA & NA \\
15 & Decanoic acid & 0.06 & NA & NA \\
16 & \(\alpha\)-Kopane & 0.04 & NA & NA \\
17 & \(\beta\)-Element & 0.20 & NA & NA \\
18 & \(\beta\)-Kubeben & 0.06 & NA & NA \\
19 & \(\beta\)-Caryophyllene & 0.08 & NA & NA \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Chemical composition of chamomile essential oil. In amounts above 1% in the EO, there were \(\alpha\)-bisabolol B oxide (5.92%) (in the literature: 3-50%), trans-isopropylobicycloon-3-en-8-one (4.26%), isomers 2-(2,4-hexadinilidene)-1,6-dioxa-spiro [4,4]non-3-ene (2.83% and 0.16%), \(\beta\)-farnesene (1.39%), and \(\beta\)-cubebene (1.23%), which are not provided in the literature as the main compounds contained in the oil. Among the effects reported in the literature as a consequence of this oil, the following were not detected: en-yn-dicycloether, n-octanal, 1,8-cineo, \(\alpha\)-terpineol, germacrene D, and polyacetylene derivatives. Regarding the literature data, these compounds occur in