esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results  
### Energy Demand  
Firstly, we computed the energy demand of each building model for each location and construction year. Table 6 summarises the results of the simulation for the reference set-point temperatures. The values represent the expected heating and cooling demand of the oldest and newest building stock in peninsular Spain. On average, the energy level demand was reduced by 72.1% for heating and 45.7% for cooling as a result of the new building code, quantifying the potential of savings by renovating the old building stock. The results showed that single-family buildings had a higher demand than multifamily buildings. This difference is justified by the lower compactness that is a characteristic of \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Energy Demand**} & \multicolumn{2}{c}{**Single-Family Buildings**} & \multicolumn{2}{c}{**Multifamily Buildings**} \\ \cline{3-6}  & **(kWh/m\({}^{2}\)Year)** & **1979** & **2019** & **1979** & **2019** \\ \hline \multirow{3}{*}{Heating} & Max. & 161.5 & 53.0 & 91.1 & 38.6 \\  & Avg. & 68.1 & 21.1 & 42.7 & 13.8 \\  & Min. & 14.6 & 0.8 & 8.9 & 0.4 \\ \hline \multirow{3}{*}{Cooling} & Max. & 50.7 & 22.0 & 26.2 & 16.0 \\  & Avg. & 22.0 & 9.4 & 11.3 & 7.5 \\ \cline{1-1}  & Min. & 5.6 & 2.1 & 3.0 & 2.0 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Energy demand for the reference set-point temperatures by building typology and construction year: maximum, average, and minimum values.
# Evaluation of Condition of Concrete Structures Using Ultrasonic Pulse Velocity Method
## 3 Ultrasonic Pulse Velocity Method
To calculate the average ultrasonic pulse velocity in concrete at early ages, the ultrasonic pulse velocity was measured 20 times at the center of the specimens, as shown in Figure 2, using ultrasonic pulse velocity measuring equipment from Olson in the U.S. in accordance with the standards of KS F 2731 and ACI 228-2R based on the ages of 16, 20, 24, 48, 72, 120, 168, 360, and 672 h. For the compressive strength of concrete, the experiment was performed in accordance with KS F 2405, as shown in Figure 3.  
The top surfaces of the specimens were polished using a grinder for testing the compressive strength. The compressive strength was calculated after measuring the maximum load using a digital universal testing machine (UTM). The results of the experiment conducted for the 123 fabricated specimens to estimate the compressive strength of concrete using the ultrasonic pulse method are as follows. For the designed strength of 24 MPa, the ultrasonic pulse velocity in each specimen was measured at the ages of 16, 20, 24, 48, 72, 120, 168, 360, and 672 h, and compressive strength testing was conducted. The measurement results are listed in Table 2. The measured ultrasonic pulse velocity for the designed concrete compressed strength of 24 MPa was 96.4 m/s at 16 h of age, 709.8 m/s at 20 h, 1005.3 m/s at 24 h, 2300.1 m/s at 48 h, 2703.5 m/s at 72 h, 2988.8 m/s at 120 h, 3131.9 m/s at 168 h, 3382.6 m/s at 360 h, and 3381.1 m/s at 672 h. Figure 4 shows the ultrasonic pulse velocity according to age. As shown in the Figure 4, the wave velocity sharply increased from 16 to 72 h of age. It slowly increased to 120 h and then maintained a very slow increasing tendency up to 672 h.  
Figure 3: Testing method for compressive strength of molded concrete cylinders. Figure 2: Experiment of ultrasonic pulse velocity method.
## 2 System Modeling
### Modeling of Permanent Magnet Synchronous Generator  
The PMSG has two primary purposes: to convert mechanical energy to electrical energy usable for the grid and to apply torques to the turbine system that oppose \(T_{turbine}\) to control the speed of rotation.  
For PMSGs, it is common to utilize a rotating reference frame to model and control the machine. Following the power-invariant d/q transformation presented in [29], electromagnetic torque \(T_{gen}\) can be calculated as shown in (5), where \(p\) is the number of poles, \(\lambda_{r}\) is the rotor flux linkage, \(L_{d}/L_{q}\) are the d-/q-axis stator inductances, and \(i_{d}/i_{q}\) are the d-/q-axis stator currents. In this work, it is assumed that there are no losses in the PMSG, such that \(T_{gen}\) is equal to the torque applied on the shaft of the PMSG rotor.  
\[T_{gen}=\frac{p}{2}\big{(}\lambda_{r}-(L_{d}-L_{q})i_{d}\big{)}i_{q} \tag{5}\]  
Assuming the voltage at the DC bus of the power electronic converter is sufficiently high such that the d/q voltages do not exceed the achievable per-phase voltage at the stator terminals, no field weakening is required, and \(i_{d}\) can be set to 0 [29]. In this case, (5) can be simplified further, resulting in the following relationship between q-axis current and torque:  
\[T_{gen}=\frac{p}{2}\lambda_{r}i_{q} \tag{6}\]  
Following the power-invariant d/q transformation, the root mean square (RMS) per-phase current \(I_{ph}\) can be calculated from the q-axis current as follows:  
\[I_{ph}=\frac{\sqrt{i_{d}^{2}+i_{q}^{2}}}{\sqrt{3}}=\frac{i_{q}}{\sqrt{3}} \tag{7}\]
## 3 RS Applications in Ocean
### Ocean Wave Height (OWH)
#### 3.3.2 Sar  
SAR is a unique system for OWH observation from space because it has a high spatial resolution (e.g., 1-10 m), broad coverage, and it is independent of cloud cover and light conditions [164]. SAR uses the omitted backscattering signal from the ocean surface to measure OWH [165]. Theoretical and empirical algorithms are two main techniques that have been employed for OWH estimation using SAR images [166]. Theoretical algorithms, standing on the SAR wave mapping mechanism (i.e., nonlinear velocity bunching, tilt modulation, and hydrodynamic modulation), invert the SAR intensity spectrum into a wave spectrum [167]. The semiparametric retrieval [168], parameterized first-guess spectrum [169], and partition rescaling and shift [170] are three well-known theoretical-based algorithms for OWH estimation using SAR data. On the other hand, empirical algorithms, which do not need prior information of wind and wave, can directly estimate OWH from inputs generated from SAR images [171]. C-band WAVE models for European Remote Sensing (ERS)-2 [172], Envisat [173], and Sentinel-1 [174], as well as the X-band WAVE model [175] for TerraSAR-X, are some examples of the empirical algorithms.  
Among SAR systems, Sentinel-1, which provides open-access imagery with dual-polarization, has been widely used for OWH estimation. For instance, [PERSON] et al. [176] used a semiempirical algorithm along with Sentinel-1 imagery (C-band VV-polarization) for OWH retrieval. The results illustrated that the algorithm could successfully estimate OWH with an RMSE of 18.6.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**RS System** & **RS System (Type)** & **Advantage** & **Disadvantage** \\ \hline Passive & GNSS-R & High temporal and spatial resolution, all-weather capability, low cost & High dependency on the angle of incidence, relatively low accuracy \\  & & High spatial resolution, image-based & \\  & SAR & measurement, significantly less affected & \\  & & by the atmosphere, all-day and & \\ Active & & weather capability & \\  & & Large swath width and global coverage, & \\  & & data availability of four decades, & \\  & & nadir-looking geometry, range-based & \\  & Altimeter & estimation, relatively insensitive to cloud & \\  & & droplet size and rainfall rate, better & \\  & & spatial resolution in the & \\  & & along-flight direction & \\  & HF radar & Reasonable accuracy at different wind & \\  & & speeds, large scale coverage & \\  & & High spatial and temporal resolutions, & \\ Marine radar & & cost-effective, better SNR ratio, not & \\  & & affected by atmospheric conditions & \\ \hline \hline \end{tabular}
\end{table}
Table 3: Different RS systems for OWH estimation along with their advantages and disadvantages.
## 1 Introduction
This paper investigated sensitivities of ecosystem-scale WUE to phenological factors in the terrestrial ecosystems of the Northern Hemisphere during the past 14 years using satellite-based products, and tried to identify response patterns of WUE to phenology across different PFTs. Achieving these objectives is a helpful step toward improving our understanding and predictions of variabilities of carbon and water cycles.
# Connected Vehicles: Technology Review, State of the Art, Challenges and Opportunities
## 6 Conclusions and Future Discussion  
CVs technology brings some challenges and opens up new possibilities, applications, and services. These innovative applications and services range from the shift towards keyless vehicles to digital parking maps to smart traffic management and eco-friendly environments. This originates from the abundance of in-vehicle sensing and improvements in onboard computation processing, networking, and communication, which paves the way for innovative applications that guarantee a safer, convenient, and more environment-friendly driving experience.  
This study provided a deep dive and a comprehensive review of CV technologies and shed light on key enabling technologies, such as DSRC and 5G cellular communications. A precise look over the latest status quo and industrial directions on each of these technologies was presented to the reader. We introduced and provided recommendations about the technical challenges associated with CVs technology in terms of OTA, privacy, security, integration of computation, and communication issues. We also provided analytical discussions on safety and non-safety applications and drew the attention of the research community towards open challenges and promising applications that can greatly enhance traffic efficiency and operations. Future opportunities and research directions were highlighted, which will assist CV technologies to bring a more prosperous future to humanity.  
Data curation, G.A. and K.E.; Investigation, A.K. All authors have read and agreed to the published version of the manuscript.  
We acknowledge the support of the Natural Sciences and Engineering Research Council of Canada (NSERC), [funding reference number CRC-2017-00170].  
Not applicable.  
The authors declare no conflict of interest.
# Greening the NetFPGA Reference Router
## 4 Frequency Control Policies for Dynamic Frequency Scaling
### Single-Threshold Policy  
Due to the finite queue size, the STP is to assess an associated traffic throughput threshold beyond which the router will begin to loss packets for each operating frequency. Table 1 presents the mapping table of operating frequencies, capacity states, measured capacities and preset thresholds for STP.  
Figure 3: Implementation of dynamic frequency scaling on the frequency-scaled router (FSR).  
As shown in Figure 4, the capacity states \(S_{1}\), \(S_{2}\), \(S_{3}\), \(S_{4}\) and \(S_{5}\) represent the routing capacities of the FSR working at core operating frequencies of 7.8 MHz, 15.6 MHz, 31.3 MHz, 62.5 MHz and 125 MHz, respectively. \(C_{j}\) represents the peak measured throughput for each capacity state \(S_{j}\). At 125 MHz, the peak measured throughput \(C_{5}\) is below the theoretical full operation throughput 4 Gb/s, which is the maximum throughput for the NetFPGA router. For each capacity state \(S_{j}\), the threshold \(T_{j}\) should not be preset too aggressively and too close to \(C_{j}\). Because the statistics monitoring is implemented by counting bytes at a fixed sampling period and the statistics may vary slightly from time to time, thus \(T_{j}\) must be set lower than \(C_{j}\), and experiments indicate that a reasonable value for \(T_{j}\) is 95% of \(C_{j}\). A level of 95% was chosen for consistency with prior work on ALR [1], as was the 10-ms sampling period. The choice of these parameters involves a trade-off between energy savings and packet loss.  
Suppose that the FSR is working in state \(S_{j}\) (\(j=1\) to 5); once the total number of bytes received from all receive queues (which is checked at 10-ms intervals) is below or equal to a threshold \(T_{i}\) (\(1\leqslant\) i \(\leqslant\) j - 1), the router can switch to the lower capacity state \(T_{i}\) consuming less power while maintaining QoS. On the contrary, if the total number of bytes received from all receive queues is beyond the threshold \(T_{k}\) (k \(\geqslant\) j), the router must switch to the higher capacity state \(S_{k+1}\) (\(1\leqslant\) k \(\leqslant\) 4) with more power consumption to avoid packet loss resulting from queue overflow. Otherwise, the router stays in the current capacity state \(S_{j}\). Figure 5 presents the flowchart of the STP.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Frequency** & **State** & **Capacity** & **Threshold** \\ \(f\) **(MHz)** & \(S_{i}\) & \(C_{i}\) **(Bytes)** & \(T_{i}\) **(95\% of \(C_{i}\)) (Bytes)** \\ \hline
7.8 & \(S_{1}\) & \(C_{1}\) : 554 K & \(T_{1}\) : 526 K \\
15.6 & \(S_{2}\) & \(C_{2}\) : 1098 K & \(T_{2}\) : 1043 K \\
31.3 & \(S_{3}\) & \(C_{3}\) : 2143 K & \(T_{3}\) : 2036 K \\
62.5 & \(S_{4}\) & \(C_{4}\) : 4321 K & \(T_{4}\) : 4105 K \\
125 & \(S_{5}\) & \(C_{5}\) : 8620 K & \(T_{5}\) : 8190 K \\ \hline \hline \end{tabular}
\end{table}
Table 1: Frequency, capacity and threshold mapping table for the single-threshold policy (STP).  
Figure 4: Thresholds of the single threshold policy.  
Figure 5: Flowchart of the single-threshold policy.
## 5 Experimental Evaluation  
Two sets of experiments have been performed, first, adding extra noise to every bit 1 and adding selective noise. Mostly, these experiments are implemented by using a multi-core simulator, Sniper-v7.2 [10; 11], as a fast and reliable simulator for multi-core [47]. McPAT-v1.0 is integrated as the power model. McPAT is an integrated power, area, and timing modelling framework for multithreaded, and many-core/multi-core architectures [48]. This analysis has been done in order to thwart the covert thermal channel attack of our targeted device. To covertly transmit sensitive information from a secured zone to a non-secured one, the thermal covert channel programs require generating and measuring temperature signals by using the HotSpot simulator. We chose the Hotspot-v6.0 thermal model to dynamically produce temperatures for all the cores. We adopt a few benchmarks from PARSEC and SPLASH-2 and their temperature signals will be treated as the thermal noise to a thermal covert channel. The experimental setup uses Sniper and Hotspot simulation tools and TCC programs. Their configuration details are now tabulated in Table 2. The floor plan of the processor cores follows the one reported in [3; 5]. As Table 2 shows, the transmission frequency of the TCC dynamically changes with a range of 10 Hz, 50 Hz, 150 Hz, and 200 Hz, etc., and the working CPU frequency of the transmitter/receiver core is 2000 MHz. In addition, it is identified whether there is a TCC attack or not. If an attack is found, the position of the transmitters/receivers associated with the thermal covert channels are required to be found. This positioning accuracy is referred to as \(P_{acc}\). \[P_{acc}= \begin{cases}1&P_{detected}=P_{transmitter}//receiver\\ 0&\text{otherwise}\end{cases}  \tag{1}\]  
where:  
Figure 7: The process of adding selective noise. \(P_{detected}\): is the position (core id) of the detected thermal covert channel transmitter/receiver cores. \(P_{transmitter}\): is the actual position of the transmitter/receiver cores. Table 3 shows the average accuracy of positioning the transceiver in different multi-core systems, which is around 97%. By using this detection strategy, we can almost always identify a TCC attack. Table 4 illustrates that the proposed countermeasure strategy can efficiently fight TCC attacks, up to the point that with this proposed countermeasure, the average BER of the TCC attacks across \(8\times 8\) systems can be higher than 94%. An interesting fact is that the average power consumption when the selective noise is in effect does not increase significantly. The formula that is used for computing the average power consumption is as follows [47]:  
\[P_{a}vg=\frac{\sum_{c=1}^{N_{c}}(\sum_{u=1}^{N_{c}}2_{cu})}{N_{c}}[W] \tag{2}\]  
where:  
\(N_{c}\): The number of cores.
# A Review of Industry 4.0 Manufacturing Process Security Risks
## 2 A Complete Paradigm Shift
### Convergence of IT and OT
Conversely, OT devices commonly act as both servers and clients, depending on various parameters within the larger scale system of which they form a part. For example, HTTP works well with networks using a one-way control authority between devices, but is not designed for the unique nature of the control authority of which OT system networks make use. Although it is possible to implement HTTP in OT system networks, it involves adapting its use to work in applications for which it is not specifically designed, which presents its own unique set of challenges. Several new protocols have been designed to address this particular issue. One example is the new International Organization for Standardization (ISO) protocol named message queuing telemetry transport that makes use of a publish-subscribe mechanism, specifically designed to address the network communications issue between IT and OT systems. Other such protocols are the extensible messaging and presence protocol, advanced messaging queuing protocol and data distribution service [8; 9].
# In-Depth Analysis of GAF-Net: Comparative Fusion Approaches in Video-Based Person Re-Identification
## 6 Conclusions  
This study introduces GAF-Net, a novel method for video-based person re-identification (Re-ID) that uniquely integrates skeleton-based gait features with appearance information. Unlike traditional approaches, GAF-Net leverages precise movement patterns captured by skeletal data, offering robustness to clothing changes and complex backgrounds. We evaluated GAF-Net on the iLIDS-VID and MARS datasets, demonstrating its versatility across different video lengths and environments. On iLIDS-VID, GAF-Net achieved state-of-the-art performance, with 93.20% rank-1 and 99.34% rank-5 accuracies, surpassing existing methods. For MARS, despite challenges with shorter sequences, it showed competitive results, with 86.09% mAP and 89.78% rank-1 accuracy. Notably, GAF-Net consistently improved upon appearance-only architectures, enhancing PiT on iLIDS-VID and MGH on MARS.  
Our findings highlight GAF-Net's potential and areas for future work. Despite excelling with long, uniform sequences, it faced limitations in diverse environments and with shorter videos. Future research should focus on improving gait feature extraction for varied conditions, developing adaptive fusion strategies, and optimizing computational efficiency. By addressing these challenges, GAF-Net can evolve into a more robust and practical Re-ID system, advancing real-world applications in security and surveillance. As the field progresses, we anticipate Re-ID methods that perform well across diverse scenarios, significantly impacting smart city technologies.  
Conceptualization, M.B., R.I., L.N., D.M. and S.D.; methodology, M.B., R.I., D.M. and S.D.; software, M.B.; validation, M.B., R.I., D.M. and S.D.; formal analysis, M.B., R.I., D.M. and S.D.; investigation, M.B.; writing--original draft preparation, M.B.; writing--review and editing, M.B., R.I., L.N., D.M. and S.D.; visualization, M.B.; supervision, R.I., L.N., D.M. and S.D.; project administration, R.I., D.M. and S.D. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding authors..  
The authors declare no conflicts of interest.
# A Survey of Data Representation for Multi-Modality Event Detection and Evolution
## 5 Multi-Modality Data Representation and Event Detection
### Other Methods  
There are also some other data representation methods for multi-modality event detection, which cannot be categorized into the above categories. For instance, [PERSON] et al. [102] present a shared multi-view data representation (SMDR) model for multi-domain event detection that learns the intrinsic structures between different data views. [PERSON] et al. [103] combined the textual and visual information by nonlinear Canonical Correlation Analysis (CCA), in which the LSTM is used to pre-encode the textual and visual features and multi-layer perceptron with a residual link. There are also some methods based on hashing that obtain features of multi-modal data. In these methods, different modalities are projected into a commonly shared space. For example, [PERSON] et al. [104] proposed a method to retrieve a list of historical event summaries, in which high quality event representations is extracted by using the temporal query expansion technique. [PERSON] et al. [105] proposed a multimodal topic and-or graph (MT-AOG), which can be used to represent important textual and visual elements of news stories. MT-AOG models latent topic structures by leveraging a context sensitive grammar that can describe the hierarchical composition of news topics by semantic elements about people involved, related places, and what happened.  
The advantages and disadvantages of the multi-modality event detection methods are shown in Table 3.  
It can be seen from Table 3 that all models have some advantages, but the disadvantages of some models are not introduced, mainly because most of these models are applied to specific scenarios and solve specific application problems. Since the researches in the field of multi-modality event detection faces different scenarios and the problems to be solved are also different, these models are not universal. Most of the researches are carried out on the self-collected datasets, so it is difficult to evaluate which model is the best or worst. Only a small number of studies were evaluated under the same dataset, and their performances were compared in the evaluation part of Section 7.