esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
This study developed a hybrid modeling method for an effective analysis of an acoustic transducer array with arbitrarily shaped flexible surrounding structures. More precisely, the proposed analysis procedure is divided into two parts: The first part is for the construction of the impedance matrix using an EC model and a FE-BE coupling model. We derived the electro-mechanical-acoustic coupling impedance matrix equation and established the procedure of calculation of the impedance matrices. Specifically, the mechanical and electrical impedances were derived from the LPM and T-network, a type of the EC model. The acoustic radiation impedances were calculated from the FE-BE coupling model, which represented the surrounding structure and acoustic coupling. The second part is dedicated to the construction of the acoustic transfer matrix using the FE-BE coupling method. Here, the acoustic pressure on each head surface can be calculated using the acoustic radiation impedance and the head velocities. The far-field acoustic pressure can be also evaluated by the acoustic transfer matrix equation and the head velocities.  
The proposed method was applied to sonar with 96 tonpliz transducers and surrounding structures. The response of each transducer was calculated (such as the electrical admittance and the vibration velocity) along with the array performance (such as the far-field directivity pattern and the TVR). The results were compared with the results of FEM software. The results showed good agreement. To evaluate the numerical performance of the proposed method, the DOFs of the FE-BE models and the full FE model were investigated and compared. The DOF reduction rate of the proposed method to the conventional FEM is increased as the analysis frequency, array size, or size of the surrounding structures increased.  
The main conclusion is that this proposed hybrid method can be used to effectively estimate the performance of the array while taking into account the surrounding structure and acoustic medium coupling. The computational effort is significantly reduced with the equivalent accuracy to the conventional FE analysis. Therefore, the proposed method is expected to be useful for conceptual design that require frequent design changes.  
Conceptualization, M.-J.S.; Formal analysis, M.-J.S., C.H., and W.-B.J.; Investigation, M.-J.S.; Methodology, M.-J.S.; Project administration, C.H.; Software, M.-J.S.; Supervision, C.H. and W.-B.J.; Validation, M.-J.S. and C.H.; Visualization, M.-J.S.; Writing--original draft, M.-J.S.; Writing--review and editing, C.H. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Figure 16: Ratio of DOFs.
## 3 Results and Discussion
Additionally, since the chart is to be used in combination with metallic coupons (acting as sensitive materials for the environment), the materials of the chart should also be inferred to the metal coupons. In order to check these aspects, the four candidate materials have been subject to the Oddy Test. Based on these results, which can be found in detail in a related work by the authors [11], acid-free laminated paper has been chosen, considering the balance between color stability and emission of harmful pollutants. Thus, considering the facts above, the most suitable material for building the calibration display has been the acid-free laminated paper. Its chromatic stability is the best ones among all the tests, whilst fulfilling the real-life safety requirement. The calibration process for the crowdsourced images can be therefore considered as safe to perform for a prolonged time. Having decided the definitive materials for building the charts, one has been printed to evaluate its suitability to endure the disparity effects on crowdsourced imaging. Six pictures with different phones, as outlined in the previous section, have been taken in the lab and the CIEDE2000 differences for each color patch extracted. Also, the standard deviation for all the metrics corresponding to the same patch has been calculated (Table 15). As seen there, not only the quality metrics are excellent, but also the standard deviation is close to 0, meaning the color calibration is adequately performed on every picture and there is and extremely low variability between the processed images, regardless of their camera of source. In Tables 16 and 17 the accuracy of the calibration scheme thanks to the robustness of the chart is demonstrated. The average digital L*, a* and b* coordinates for the color patches of each calibrated picture have been extracted and compared with measurements from the printed chart made with the spectrophotometer. Their extreme similarity in all cases reveal the good performance of the calibration scheme, which is allowed with the robust printing on the chart.
## 7 Conclusions  
This paper is based on the civil air defense project at the intersection of Zhongzhou Middle Road and Shachang South Road in Luoyang City. In order to study the influence of various factors on civil air defense construction vibration under vehicle load, first refer to the actual project on site, then use ANSYS to conduct numerical simulation calculation, and finally use the grey correlation method to conduct sensitivity analysis on the elastic modulus of concrete, thickness of overburden layer, density of soil layer, elastic modulus of soil layer, vehicle speed, and vehicle mass. The following conclusions are obtained:  
1. The displacement, velocity, and acceleration at the mid \(-\)span position of the civil air defense roof are the largest, and they are smaller and smaller along the roof from the mid \(-\)span position to the wall;
2. It can be seen from the field monitoring that when the vibration acceleration is less than \(\pm 100\) mm \(\cdot\)s\({}^{-2}\), the impact of vehicle traffic on the excavation is small, but when the acceleration is more than \(\pm 100\) mm \(\cdot\)s\({}^{-2}\), the impact is obvious, and there are adverse effects such as sand loss;
3. The grey correlation degree of the influencing factors of displacement and velocity is density of soil layer, vehicle mass, vehicle speed, elastic modulus of concrete, elastic modulus of soil layer, and thickness of overburden layer from large to small. The grey correlation degree of the influencing factors of acceleration from large to small is the vehicle mass, density of soil layer, vehicle speed, elastic modulus of concrete, elastic modulus of soil layer, and thickness of overburden layer;
4. The density of soil layer, vehicle mass, and vehicle speed have a great impact on the displacement, speed, and acceleration of civil air defense construction, with the grey correlation degree of 0.7951-0.9993.  
Conceptualization, H.Z. ([PERSON]); methodology, Y.W.; software, Y.W.; validation, Y.W. and C.M.; formal analysis, Y.W.; investigation, H.Z. ([PERSON]); resources, C.M.; data curation, Y.W.; writing--original draft preparation, Y.W.; writing--review and editing, Y.W.; visualization, Y.W.; supervision, C.M.; project administration, C.M.; funding acquisition, C.M. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Postgraduate Scientific Research Project for Anhui Universities (YJS20210393).
## 2 Characterization of Damage Model and Hydro-Mechanical Properties Model
### Damage Model in Rock creep Process
\[f_{d}\Big{(}Y_{d}^{p},d\Big{)}=d_{c}\text{tanh}\Big{(}B_{d}Y_{d}^{p}\Big{)}-d \leq 0 \tag{4}\]  
In Equation (4), \(d_{c}\) is the maximum critical value of the damage variable, and \(B_{d}\) is the parameter that controls the rate of damage evolution. \(Y_{d}^{p}\) is the driving force for the evolution of rock damage, expressed as Equation (5):  
\[Y_{d}^{p}=-\frac{\partial\Psi}{\partial d}=\frac{1}{2}(\epsilon-\epsilon^{p}) :\mathbb{C}^{\prime}(d):(\epsilon-\epsilon^{p})+\bigg{(}\gamma_{p}-\Big{(}1- \alpha_{p}^{0}\Big{)}B\ln\frac{B+\gamma_{p}}{B}\bigg{)}, \tag{5}\]  
It can be seen that the expression of the damage-driving force is a function of plastic shear strain \(\gamma_{p}\), indicating that once micro cracks undergo dislocation, it will cause the evolution of damage. We assume that the total damage in the creep property test of rock is \(\omega\), then the total damage \(\omega\) can be expressed as the sum of instantaneous damage \(d\) and time-dependent damage \(\zeta\), presented in Equation (6). \[\omega=d+\zeta, \tag{6}\]  
The equilibrium state function \(\overline{\zeta}\) of rock time-dependent damage variables can be defined as being associated with the plastic hardening function. In creep property tests, \(\alpha_{p}\) is the plastic hardening function, which is related to the internal friction angle of the material and is a function of plastic deformation. It is used to describe the plastic hardening phenomenon during plastic deformation, and can be expressed as Equation (7):  
\[\alpha_{p}=\alpha_{p}^{0}+\left(1-\alpha_{p}^{0}\right)\frac{\gamma_{p}}{B+ \gamma_{p}}, \tag{7}\]  
where \(B\) is the parameter that controls the hardening rate of the material; \(\alpha_{p}{}^{0}\) is the parameter that controls the position of the initial plastic surface of the rock; and \(\gamma_{p}\) is the plastic shear deformation value. Let \(\overline{\zeta}=(1-\omega)\alpha_{p}\). The time-dependent damage expression in the elastoplastic creep damage constitutive model of rock can be obtained as below:  
\[\zeta=\overline{\zeta}\big{(}1-e^{-\gamma t}\big{)}=(1-\omega)\alpha_{p}\big{(} 1-e^{-\gamma t}\big{)}, \tag{8}\]  
In Equation (8), by describing the time-dependent damage variable in the creep process, an elastoplastic creep damage constitutive model that would describe the creep mechanical properties of rock can be established.
## 6 Experimental Setup
### Dataset  
The Urdu web queries dataset described in Section 3 was used in all the experiments of intent detection. Table 7 shows the division of the intent annotated dataset into train and test sets. The dataset was divided using a standard ratio of 80:20. The 20% testing dataset was further divided into the testing and development sets with each having 10% of the data. The training dataset contained 6818 queries of which 5195 were informational, 677 were navigational and 946 were of a transactional intent. The testing and development sets had 850 queries each, having 650, 84 and 116 informational, navigational and transactional intent queries, respectively.
# Interoperability between Building Information Modelling (BIM) and Building Energy Model (BEM)
## 3 Results and Discussion
### IFC Import Results  
#### 3.2.1. Residential Case in CYPETHERM HE  
Although CYPETHERM HE enables IFC import directly in the software, it has been analysed that it is better to use the IFC exported from an Open BIM Analytical Model. When the IFC file was imported in CYPETHERM HE directly from Revit, all the thermal zones showed 0 m\({}^{2}\) and 75 m\({}^{3}\). However, after exporting the IFC from the Open BIM Analytical Model and importing it into CYPETHERM HE, the thermal zone dimensions were not accurately transferred. The dining room thermal zone presented the biggest difference from Revit, as its volume was 180% bigger than in the BIM. The other zones, in turn, were about 6% to 12% bigger than in Revit.  
Another problem found was the creation of two internal walls in the group of external walls that could not be deleted. In addition, the floor that was in contact with the ground was not transferred and, so, CYPETHERM HE considered this floor as a slab between floors, which could be a relevant issue when analysing the building energy demand. In contrast, all windows were properly imported, according to their dimensions, with only one window missing (see Figure 9).  
Similarly to Open Studio, it is possible to edit the materials of the building envelope and to delete and add thermal zones in CYPETHERM HE. However, once a thermal zone or a building surface is added, it cannot be referred to as specific space and, so, it is pointless to make any change, in this aspect, in CYPETHERM HE. If there is necessity for modifying the model geometry or thermal zones, it can be done in the BIM authoring tool, or in another CYPE software called IFC Builder.
# Securing Network Traffic Classification Models against Adversarial Examples Using Derived Variables
## 3 AE Impact on Network Traffic Classifiers
### Domain Constraints in AE Generation  
The feasibility of adversarial attacks differs depending on the domain, as it is highly restricted by several constraints, which can be divided into two distinct groups [52]: syntactic constraints and semantic constraints. All the constraints related to syntax are often referred to as syntactic constraints. [PERSON] et al. [53] stated three syntactic constraints that an AE must satisfy: out-of-range values, non-binary values, and multi-category membership. The values considered out of range are those that are higher than the theoretical maximum value that cannot be exceeded. Nonbinary values are entries that invalidate a feature's binary nature, whereas multi-category membership values cannot be one-hot encoded.  
However, semantic links represent the relationships that distinct features may have with each other. [PERSON] et al. [54] suggested an obvious method for NIDS by splitting the features into roughly three distinct groups with various semantic relationships. The first group comprises features that can be directly altered by the adversary (e.g., number of forward packets, size of the forward packets, and flow duration). The second group of features is dependent on the first feature and is updated with respect to the latest feature (e.g., number of packets/second, average forward packet size). The last group of features comprises elements that the adversary cannot change (e.g., IP address and protocol number).
## 6 Conclusions  
This paper aims at regulating network daily load curves and reducing distributed power system transmission loss by optimizing domestic electric vehicle charging loads. To achieve this, this paper first analyzes the key factors that can affect the charging behavior of domestic electric vehicles. In this part, for the first time in the context of domestic electric vehicles, seasonal factors are considered to model the electrical charging loads of a single domestic electric vehicle. Then, a cluster of domestic electric vehicle charging loads of the given network is modelled by the Monte Carlo method. After that, the 0-1 integer programming method is proposed to regulate network daily load curves and to reduce distributed power system transmission loss.  
The optimization results show that with the connection of electric vehicles to the grid, the peak-valley gap of the given network can increase by about 33% and the voltage fluctuation rate can increase by about 50% on average. In addition, the average network transmission loss rate for one year increases to 3.65%, which is about a 13.06% increase. To reduce the peak-valley gap, the voltage fluctuation rate, and the average network transmission loss rate of the given network, the 0-1 integer programming method is employed to optimize electric vehicle charging loads. By applying the proposed electric vehicle charging strategy, both the peak-valley gap and voltage fluctuation rate of the network can be reduced by about 45% compared with not connecting electric vehicles to the grid. Additionally, the average network loss rate for one year drops to 3.50%, which is about a 4.11% reduction in average compared with not applying the 0-1 integer programming. Furthermore, with taking seasonal factors into account, network transmission loss rates can be reduced to 3.45%, and the best time to charge electric vehicles is vastly different when compared with ignoring seasonal factors.  
In summary, the proposed 0-1 integer programming method does have good performance in reducing the network peak-valley gap, the voltage fluctuation rate, and transmission loss. Moreover, with taking seasonal factors into account, network transmission loss rate can be further reduced and the optimal electric vehicle charging time can be significantly different. Therefore, it is important to consider seasonal factors when optimizing electric vehicle charging loads. To further improve the commercial utility of the work, it is worth considering financial incentives and price signals when scheduling residential charging loads in the future work.  
This paper is funded by \"Research on multistage regulation key technology of demand response based on composite information\" of SGCC (YDB17201500163). [PERSON] designed the study; [PERSON] and [PERSON] collected the data; [PERSON] conducted the simulation; [PERSON] analyzed the data; [PERSON] wrote the paper.
## 4 Discussion
The texts included information about medical conditions, procedures, and hospital admissions with corresponding dates and medication lists. Such information could potentially be used to re-identify patients, especially in rural areas with low population densities. However, such details are crucial for HCPs to make informed decisions in primary use. Therefore, the _Masketeer_ algorithm intentionally keeps such information, albeit at the cost of privacy. [PERSON] et al. opted for a similar rationale in their Philter algorithm [9]. However, to address this at least partially in _Masketer_, geographical references to medical sites and doctor's offices are removed, limiting the risk for re-identification. On the other hand, implementing the FullName and DoubleMasker _Maskers_ improved privacy at the cost of a small number of false positives (FP rate = 0.067). For example, in the phrase \"_ann Nachmittag macht Frau [PERSON] Spaziergang_\" (meaning \"_during the afternoon_, _Mrs. [PERSON] goes for walk_\", including a missing article prior to \"_walk_\") the word \"_Spaziergang_\" (\"_walk_\") was removed by the FullName _Masker_, which wrongly interpreted \"_Spaziergang_\" as a name since it represented an upper-case word following a name. Such cases were rare and mostly occurred in notes including typing errors. Although the tool's performance was satisfactory for our use case, opportunities for further research present themselves. Future work might include the compilation of additional publicly available sources for HCP names by web scraping, which would improve _Masketeer_ in other contexts out of the box. Also, the name dictionaries could be cross-referenced with lists of syndromes named after people (e.g., [PERSON] syndrome, Austin-Flint syndrome, Dressler syndrome). Currently, these would be removed if their names occur in any dictionary, which could be addressed by extending the name whitelist described in Section 2.2.4. (NameDictionary _Masker_). Furthermore, the masking ensemble's voting logic could be improved at the cost of execution speed. By querying all _Maskers_ instead of stopping at the first one to vote, a decision could be made based upon which_Masker_ fits best with the NER, eliminating the influence of the voting order. Analyses concerning the effect of this approach on runtime and pseudonymization performance is pending. Using LLMs not only to interpret but also de-identify medical free text has successfully been demonstrated in a recent study in 2023 [29]. Engineering prompts for an LLM to identify our corpus and comparing the results to _Masketer_'s performance is also considered a matter for future research. LLMs have been shown to leak private information from their training sets [30; 31], which must be considered to protect patient PHI.
# A High Full Quality CMOS Image Sensor for Space Applications
## 2 Sensor Architecture
### Proposed Pixel Design with Multiple Charge Transfer  
Figure 2a,b show a simplified schematic and layout of the proposed pixel. The pixel is similar to a conventional 4T pixel except that a single MOS transistor is added to the floating diffusion (FD) node as a charge storage capacitor for the multiple charge transfer technique.  
The pixel maintains beneficial properties of the conventional 4T pixel, such as low noise operation and high fill factor, unlike other specified pixel architectures for WDR operation [10; 25]. Also, the pixel routing is simpler than in other WDR pixels because no additional control signal is required. In general, the FWC is limited by PPD capacitance, which depends on the PPD size and doping profile [26; 27]. The PPD capacitance can be increased by expanding its size and adjusting the shape of the photodiode itself [4]. However, p-n junction capacitance of photodiode per unit area is not sufficient to increase the considerable amount of FWC within the limited pixel size. Increasing the doping profile of the PPD increases the PPD capacitance and FWC by reducing the depletion depth between the PPD and the substrate. However, only controlling the PPD doping cannot sufficiently increase the FWC for space applications.  
In this work, instead of directly increasing the PPD capacitance, the FWC is enhanced by transferring photo-charges to the enlarged FD node multiple times. The use of an in-pixel MOS capacitor increases the capacitance of the FD node and photo-generated charge can be linearly integrated on the FD node without information loss.  
Figure 3 illustrates a potential diagram of the pixel for the multiple charge transfer. After the reset of the PPD and FD node as shown in Figure 3a, the integration of charges generated by photon is started. Before the integrated charges of the PPD are overflowed, the charges are transferred to the storage capacitor, as shown in Figure 3b,c. Figure 3d illustrates the output signal level after the charge transfer is repeated three times. The multiple charge transfer improves the SNR because signals generated from the photo charges tend to be correlated whereas noise is uncorrelated. For example, the signal and noise are increased by a factor of N and \(\sqrt{N}\), respectively, where the N is the number of charge transfer. As a result, SNR is increased by a factor of \(\sqrt{N}\).  
Figure 3: _Cont._  
Figure 2: Proposed pixel for multiple charge transfer technique: (**a**) Schematic of the pixel; (**b**) Simplified pixel layout.