esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
The number of IoT (Internet of Things) devices is predicted to increase dramatically in the years to come and their manufacturing and maintenance, including both commercial and ecological aspects associated with these, are gaining substantial attention. One of the effective ways of addressing both these issues at a time is the energy-neutral systems, which operate with the energy harvested from their environment. To address the major problem of this system, namely the low reliability, in the current paper, we develop and study the utility of a system powered solely with the wireless power transfer (WPT) over a radio frequency (RF) channel. In the article, we propose a methodology for developing and implementing a real-life IoT application based on RF WPT. We employ the proposed methodology to develop a WPT-powered solution to sense the temperature and the angular velocity in the rotating industrial environment. First, we discuss the key trade-offs arising when selecting and developing the new components for a WPT system. Then, we present and detail our solutions and describe the results of their evaluations. Finally, we instrument and evaluate the complete system, proving that it is capable of meeting all the design goals and requirements. The results reported in this paper can be of interest to the practitioners, for whom they provide a step-by-step methodology of WPT application development with a practical example. In addition, these results may be valuable for analysts, as they demonstrate many practical interrelations and effects specific to the real-life WPT applications.  
wireless power transfer; radio frequency; energy harvesting; low power technology; green IoT; application; methodology +
Footnote †: This paper is an extended version of our paper published in [PERSON]. [PERSON], [PERSON] and [PERSON], Experimental RF-Signal Based Wireless Energy Transmission. In Proceedings of the European Conference on Networks and Communications (EuCNC 2017), Oulu, Finland, 12-15 June 2017.
# Securing Construction Workers' Data Security and Privacy with Blockchain Technology
## 3 Methodology  
This study proposed a blockchain system architecture designed to safeguard the privacy and security of personal information for construction workers, particularly their biographic and safety data. The approach involved securely storing hypothetical biodata and safety data and managing this information using the proposed blockchain system. The biodata of workers adhere to the European Union's General Data Protection Regulation  
Figure 1: Data structure of a block in a blockchain.  
(GDPR), including certain details, such as names, ages, addresses, identification numbers, qualifications, certifications, and employment records. The safety data include scores of the risk level based on the joint angle information from the image process using image-based motion capture technology and occupational assessments using the Rapid Entire Body Assessment (REBA) observational tool [90; 91] to evaluate the risk of musculoskeletal disorders.  
This system utilized the Hyperledger Fabric blockchain on the AWS cloud platform, thus ensuring decentralization and immutability. The outcome was a robust information management model that enhances the privacy and safety of construction workers' data. This model permits authorized construction stakeholders to access trustworthy and verified data, thereby enabling informed decision making that prioritizes the well-being of the workers. The overall framework of this approach is depicted in Figure 2.  
This study was conducted in two phases. Phase 1 involved the experimental design of the proposed blockchain system and the storage of the workers' hypothetical biodata and safety data. Phase 1 was carried out in 4 modules. These included the implementation of Module 1, which focused on developing the blockchain using the Hyperledger Fabric platform on the AWS cloud provider. Module 2 encompassed the development of the chaincode. Module 3 involved the creation of a server-side Application Programming Interface (API), which allows client applications to send requests to the server and receive responses. Finally, Module 4 entailed integrating the blockchain system onto a third-party graphic user interface (GUI), thus enabling easy visualization of the data. In phase 2, the results from the experimental design and management of the blockchain led to the development of a conceptual information management model for enhancing the privacy and safety of construction workers' personal information and its practical implementation to validate its usability and benefits for the construction industry.
## 6 Performance Evaluation
### Simulation Model  
#### 6.1.1 Network Model  
Many studies on underwater sensor networks have proposed a cluster-based, vertical tree topology as an energy efficient network figure [29,30]. This is because the vertical tree topology reduces the number of hops required by the data for transmissions to the BS in underwater environments [31]. Thus, we also base our simulation on a cluster-based tree-topology sensor network. We assume that each node has the same number of child nodes, possibly except for the last parent node. Queries uniformly request data transmissions from all sensor nodes, and query responses are aggregated as query result messages are propagated up the tree. Every parent-child pair is assumed to be 1.5 kilometers apart (a second's distance for an acoustic wave). All queries and response messages are assumed to have average data sizes, and merged query result messages are to have larger sizes than normal query result messages (considering the additional data augmented to the payload). Additional data is added to the response payload as more queries are merged.
# Effect of Phase Noise on the Optical Millimeter-Wave Signal in the DWDM-RoF System
## 1 Introduction
Therefore, there are more parameters and more efficient techniques to be investigated to ensure an excellent system for the future. The DWDM-RoF technique is worth exploring because it generates the optical mm-wave signal using just a single modulator. Therefore, we used a DWDM-RoF architecture using a single MZM to control the phase imbalance, which causes phase noise in mm-wave signals. The DWDM-RoF architecture uses a phase shift component before the MZM to adjust the phase imbalance. The main objectives of our study were to present the DWDM-RoF architecture, generate the 60 GHz mm wave, simulate the DWDM-RoF architecture using a single MZM scheme, and demonstrate the effects of phase noise on the generated optical mm-wave signal in the DWDM-RoF system.
## Distributed Power Allocation for Sink-Centric Clusters in Multiple Sink Wireless Sensor Networks  
**[PERSON] 1, [PERSON] 1,*, [PERSON] 1, [PERSON] 1, [PERSON] 1, [PERSON] 1 and [PERSON] 2**  
1 Department of Electronic and Information, The University of Nantong, Nantong Jiangsu, China  
2 Department of Sciences, The University of Nantong, Nantong Jiangsu, China  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel.: +086-513-8501-2622; Fax: +086-513-8501-2600.  
_Received: 6 January 2010; in revised form: 21 January 2010/ Accepted: 7 February 2010 / Published: 11 March 2010_  
**Abstract:** Due to the battery resource constraints, saving energy is a critical issue in wireless sensor networks, particularly in large sensor networks. One possible solution is to deploy multiple sink nodes simultaneously. Another possible solution is to employ an adaptive clustering hierarchy routing scheme. In this paper, we propose a multiple sink cluster wireless sensor networks scheme which combines the two solutions, and propose an efficient transmission power control scheme for a sink-centric cluster routing protocol in multiple sink wireless sensor networks, denoted as MSCWSNs-PC. It is a distributed, scalable, self-organizing, adaptive system, and the sensor nodes do not require knowledge of the global network and their location. All sinks effectively work out a representative view of a monitored region, after which power control is employed to optimize network topology. The simulations demonstrate the advantages of our new protocol.  
**Keywords:** wireless communication; sensor networks; multiple sink; clustering hierarchy; power control
# Research of Enzyme-Induced Carbonate Precipitation on Strength Behavior of Reinforced Sand
## 3 Results and Discussion  
### Unconfined Compressive Strength  
#### 3.1.1 Influence of Curing Time on Strength  
The variation in UCS of EICP-reinforced sand samples with different densities and curing times is depicted in Figure 4.  
It can be seen that the strength of soil samples generally increased with curing time, peaking within the tested duration. Notably, the strength of EICP-reinforced soil samples at all densities exhibited a significant increase as the curing time extended from 1 to 3 days, due to the incomplete reaction of the cementing solution and limited calcium carbonate formation initially. After 3 days, the strength increase was marginal for the sample with \(D_{\rm r}\) = 0.9, as higher density reduced pore volume, and the calcium carbonate formed initially was less effective in filling smaller pores. For samples with \(D_{\rm r}\) = 0.8, the reaction took  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Test** & **Curing Time \(d\)** & **Relative Densities** & **Cementation \(C\)** \\  & **Day** & **\(D_{\rm r}\)** & **mol/L** \\ \hline UCS-1 & 1, 3, 5, 7, 28 & 0.6, 0.7, 0.8, 0.9 & 1.0 \\ UCS-2 & Optimal curing time & 0.6, 0.7, 0.8, 0.9 & 0.5, 1.0, 1.5, 2.0 \\ SEM & Optimal curing time & 0.6, 0.7, 0.8, 0.9 & 0.5, 1.0, 1.5, 2.0 \\ CaCO\({}_{3}\) quantify & Optimal curing time & 0.6, 0.7, 0.8, 0.9 & 0.5, 1.0, 1.5, 2.0 \\ Micro-CT & Optimal curing time & 0.7 & 0, 0.5, 1.0, 1.5, 2.0 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Test program of this study.  
Figure 4: Variation in UCS of EICP-reinforced sand with curing time.  
5 days to complete, after which no significant strength increase occurred. For samples with lower densities (\(D_{\rm r}\) = 0.7 and \(D_{\rm r}\) = 0.6), the strength peaked at 7 days, due to larger pores accommodating more calcium carbonate. Beyond 7 days, strength did not increase significantly, indicating the reaction was near completion. The ideal curing time was thus identified as 7 days, and future experiments used this duration. It was also observed that the optimum curing time decreased with higher \(D_{\rm r}\), suggesting a correlation between pore scale and calcium carbonate formation efficiency. Smaller pores may limit calcium carbonate precipitation, but further studies are needed.
# Spectroscopy Imaging Techniques as In Vivo Analytical Tools to Detect Plant Traits
## 2 Plant-Light Interaction  
To begin, an HSI and MSI system involves analyzing light-plant interaction. Understanding this interaction can help choose the proper sensor [51]. Light (electromagnetic radiation, EMR) and plant interaction depends on light frequencies [50]. For healthy leaves, photosynthetic pigments, e.g., chlorophyll, carotenoids, anthocyanin, and xanthophyll,  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Research Emphasis** & **Refs.** \\ \hline Seed viability & [37; 38] \\ Chemical compounds & [39; 40; 41] \\ Food adulteration & [10; 42] \\ Food classification & [43; 44; 45; 46; 47; 48] \\ \hline \hline \end{tabular}
\end{table}
Table 1: Application of HSI and MSI in agriculture.  
can be observed in the VIS region (400-700 nm), while the NIR region (700-1100 nm) predominantly corresponds to dry matter, and the SWIR region, within 1100-2500 nm, is mainly attributed to water [50]. [PERSON] et al. [52] stated that nitrogen and water can also be observed in the NIR and SWIR regions, respectively. As shown in Figure 1, the visible region has a lower reflection value. This is caused by the highest absorption at approximately 490 and 690 nm by chlorophyll [53]. A small peak reflection is also observed in the visible range (-550 nm), which contributes to the green color [54]. In the NIR bands, a high-sharp reflectance trend occurs, indicating a red edge, in which light absorption by leaf pigments no longer exists [54; 55]. In vegetables, the response of O-H bands is found at 1190, 1450, and 1940 nm [10]. The absorption of the first overtone of carbon-hydrogen bond could be detected between 1700 and 1800 nm [56; 57]. According to [PERSON] et al. [10], the response of C-H might be due to the presence of cellulose.  
When light passes through a leaf, there will be some interactions between the plant and light. The interactions include (i) reflection, (ii) scattering, (iii) absorption, and (iv) transmission [50; 52]. Reflection occurs when light is bounced back after entering the leaf's surface. When light is reflected by a different angle caused by a different shape of the leaf structure, it is called scattering. In terms of absorption (mathematically described as Log1/R), electrons accept photons' whole energy and are displaced to a higher configuration in the form of thermal energy. Otherwise, transmission occurs when atoms pick up the wave, vibrate briefly, transmit the vibration through the body of the leaf, and emit the wave as light at the other end. Figure 2 illustrates how light interacts with a leaf surface.  
Figure 1: Common spectral features of plants (Reprinted/adapted with permission from Ref. [51]. 2023, [PERSON], [PERSON], [PERSON], [PERSON]).  
Figure 2: _Cont._
# Securing SCADA Energy Management System under DDs Attacks Using Token Verification Approach
## 4 Trusted Encrypted Validator Module (TEVM) Based on Token Authentication
### Authentication Mechanism  
Above all, prior to CS sending out regular requests or control requests from BEMS, the TEVM would check to determine whether the token is legitimate. If the token did not exist or was illegitimate, then, CS must apply for a legitimate token and provide the required information to TBAS during application. Upon receiving the application from CS, TBAS would examine its information legality, and if legitimate, the token would be generated and sent simultaneously to CS and TEVM, if not, CS would receive a message explaining the wrong information and the need to reapply. After receiving the message from CS, TEVM determines whether the token is legitimate and consistent with that from TBAS. If so, the requested information would be sent to the PLC/IoT Device; if not, a message explaining the incorrect information would be sent to CS accompanied by a request to reapply for the token. After receiving such requests, PLC/IoT devices are required to take immediate and specific actions, and send reply messages to TEVM. Then, after receiving this reply, TEVM would examine if there was legitimate token within itself. If there was no legitimate token, it would send the requested information to TBAS to apply for a token; if a legitimate token existed, it would send the combined token and reply to CS. After receiving the application for a token from TEVM, the TBAS procedure would follow the same procedure used when CS applied for a token. Finally, when CS received information from TEVM, it would also check whether the token was legitimate and consistent with that of TBAS. If an inconsistency is found, it would reject the message and reply to TEVM with the wrong information and a request to reapply; otherwise, TBAS would save the replied information to the database. The complete procedure of the identity authentication mechanism is shown in Figure 3.
## 4 Key Technology
### Fault Handling Decision  
During the design of the constellation, the designer will give full consideration to potential fault modes and make corresponding maintenance plans. After fault diagnosis service identifies the cause, a group of maintenance plans should be selected from the preplanned maintenance plans to implement the fault. Based on the digital model, the maintenance strategy can be injected into the model in the form of parameters or modules and simulated before implementation to verify its effectiveness. In addition, the O&M personnel can also adjust the maintenance strategy predictively with the aid of status prediction to achieve optimal O&M.
## 3 Materials and Methods
### Relevance of Methodology
The iron silicate slags were subjected to the isothermal calorimetry-based rapid screening test for SCMs outlined by [PERSON] [22], further developed and referred to as the rapid, relevant, and reliable (R\({}^{3}\)) test by [PERSON] et al. [53]. The choice of this method was based on the study presented by [PERSON] et al. [54], which demonstrated that the R\({}^{3}\) test results correlated strongly with the strength of mortars, independent of the type of SCM and with great repeatability between laboratories. Furthermore, this calorimetry-based testing method tests the inherent reactivity of the SCM without the influence of cement hydration [21; 32]. A 3:1 mass-based ratio between portlandite (98% Ca(OH)\({}_{2}\)) and the ground slags were mixed together with potassium sulfate (99.99% K\({}_{2}\)SO\({}_{4}\)) on a dry basis. The amount of potassium sulfate was based on the analyzed alumina content of the original slag to achieve a 1:1 SO\({}_{3}\):Al\({}_{2}\)O\({}_{3}\) molar ratio. Pasets with 1:1 mass-based ratios of 0.5 M potassium hydroxide solution and the solid blends were mixed for 2 min at 1600 RPM using an overhead stirrer. About 15 g of the pastes was transferred to calorimeter glass ampoules and subsequently placed in a TAM Air isothermal calorimeter (TA Instruments, New Castle, DE, USA). The sealed ampoules were placed in the calorimeter within 5 min after adding the potassium hydroxide solution to the solid blends. The heat flow was recorded for 7 days at a temperature of 40 \({}^{\circ}\)C. All weights were recorded on the third decimal point. Due to the importance of the granulometric properties of SCMs [23; 24; 25; 26], the ground slags were characterized for their Brunauer, Emmett, and Teller (BET) specific surface areas. This was achieved by using a Micrometrics Gemini 2390a after degassing at 300 \({}^{\circ}\)C for 60 min using a Micromeritics FlowPrep 060 (Micromerities Instruments Corporation, Norcross, GA, USA).
# Collecting Sensed Data with Opportunistic Networks: The Case of Contact Information Overhead
## 3 A Model for Contact Information Overhead
### Impact of Contact Information Size on Message Forwarding
#### 3.2.1 Delay Incurred in Exchanging Contact Information  
Due to short-lived encounters in OppNets, it is important to forward enough data messages to the relay node before the link is disconnected. Since summary vectors need to be received before messages can be forwarded, the size of a summary vector needs to be as small as possible. Larger summary vectors would require more time to be transferred, and if the encounter duration is relatively short, some messages in the buffer may fail to be forwarded before the transmission opportunity is lost. The contact vector tends to account for a significant portion of the summary vector in terms of size, since it increases with node population and number of encounters. As a result, a reasonable amount of the delay incurred in exchanging summary vectors emanate from the size of contact vectors. Hence, less contact information contributes to higher data exchange success and vice versa. With a data transmission rate of \(R\) bytes per second on resource constrained nodes, the time, \(T_{C}\), taken for a successful exchange of contact information is given by Equation (2).  
\[T_{C}=\frac{2S_{C}}{R} \tag{2}\]  
To illustrate this, consider two nodes, A and B, each with 625 KB of messages in their buffer. Supposing summary vectors do not need to be exchanged, a usable encounter duration of 5 s (i.e., the available time after removing delay in discovering encounter events and establishing connection) should be sufficient for a successful data transfer at the rate of 250 KB per second (in an ideal state). In other words, the nodes are able to exchange 1250 KB of data (i.e., each node is able to send 625 KB and receive 625 KB), hence, 100% data exchange success. If they were to exchange 10 KB of contact information before actual data transfer, the remaining encounter duration (i.e., 5 s \(-\)\(T_{C}\) = 4.92 s) would permit a maximum of 1230 KB of data to be transferred, hence, 98.4% data exchange success. Table 1 shows the data exchange success for different amounts of contact information.
# Energy-Efficient Resource and Power Allocation for Underlay Multicast Device-to-Device Transmission
###### Abstract  
In this paper, we present an energy-efficient resource allocation and power control scheme for D2D (Device-to-Device) multicasting transmission. The objective is to maximize the overall energy-efficiency of D2D multicast clusters through effective resource allocation and power control schemes, while considering the quality of service (QoS) requirements of both cellular users (CUs) and D2D clusters. We first build the optimization model and a heuristic resource and power allocation algorithm is then proposed to solve the energy-efficiency problem with less computational complexity. Numerical results indicate that the proposed algorithm outperforms existing schemes in terms of throughput per energy consumption.  
Device-to-Device (D2D) communication; multicast transmission; energy-efficiency +
Footnote †: journal:  
0000-0001-4600-3999-4600]H.H.R.R.
## 4 Results and Discussions
### CBH Test  
The values of D of the five subsystems were calculated using the CBH test. The three engines together are shown in Table 4. Mathematically calculated values, as well as software values, are shown in the table. The test values for all five subsystems falls between the lower (0.10) and upper value (5.99). Hence, the TBF data for each subsystem of three engines pass CBH suggesting pooling of TBF data for further analysis.