esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results and Discussion
### Evaluation of Displacement Amplification Factor  
Regarding the displacement amplification factor, although the current version of the Chilean seismic design code does not consider the amplification of displacements obtained from the modal response spectrum analysis to account for the effect of reducing the elastic design spectrum through the response reduction factor (\(R\)), the displacement amplification factor \(C_{d}\) was calculated using the following expression:  
\[C_{d}=\frac{R}{\beta_{I}} \tag{11}\]  
In this equation, \(R\) is the response reduction factor and \(\beta_{I}\) is the damping coefficient, which depends on the effective damping and the structural period, as obtained according to ASCE 7-05 [79]. To determine the value of the damping coefficient, a reference period \(T_{0}=0.08\)s was considered, based on the corresponding empirical expression provided in ASCE 7-05.  
Since the fundamental periods of all archetypes in both analysis directions exceeded this value, and considering that the Chilean seismic code assumes a damping ratio of 5% for reinforced concrete buildings, the value of \(\beta_{I}\) was equal to 1.0. Applying this coefficient, the displacement amplification factors that may be used for estimating the seismic displacement and drift demands for the analyzed archetypes are those shown in Figure 20.  
Although displacement amplification factors are not currently used in the Chilean seismic code [1] for the estimation of inelastic displacements, they were applied in this study  
Figure 20: Calculated displacement amplification factors for the archetypes under study.  
to align with the output requirements of the FEMA P695 methodology. This allowed for consistency with international practices, such as those adopted in ASCE 7 and Eurocode 8. The results obtained may provide a useful reference for potential future revisions of the Chilean code. Additionally, a sensitivity analysis is recommended to assess the impact of varying the critical damping ratio from the standard 5%, in line with the provisions of ASCE 7 for adjusting the \(\beta_{1}\) factor.
# Process Mining IPTV Customer Eye Gaze Movement Using Discrete-Time Markov Chains +
###### Abstract
Our hypothesis is that the gaze movement process of participants watching IPTV satisfies the Markov assumption, which is that what the participant is gazing at now only depends on what s/he last gazed at and does not depend on the rest of the gaze history. We have created a pipeline of data analysis and modelling and come up with interpretations of created DTMC properties for specific scenarios as well as evaluation of user interface when using the BT Player on different pages. Also, we have generated a series of scripts using Java, R Studio, MySQL, etc., and relevant code scripts are now available on GitHub for reference through the link: [[https://github.com/Benedict1123/Eyetracking](https://github.com/Benedict1123/Eyetracking)]([https://github.com/Benedict1123/Eyetracking](https://github.com/Benedict1123/Eyetracking)), accessed on 18 January 2023. The study in our paper has demonstrated a comprehensive methodology to combine eye-tracking technology with IPTV products, along with machine learning techniques, to generate explainable results for the purposes of evaluating and improving the UI design of the IPTV platform. The main difference between our study and previous research in the eye-tracking and HCI fields is that we focus on the sequence in the gaze movement from the eye-tracker data, and we also introduce time into the methodology when calculating the mean passage time of a DTMC. Previous literature shows that researchers usually carry out quantitative analysis of eye tracker data such as fixation counts, fixation period, etc. The methodology in our study can be applied to other IPTV products or systems with human interactions for further research. The remainder of the paper is structured as follows. The next section talks about the research background, regarding previous related work on applications of eye tracking technology, human-computer interactions, Markov Modelling, etc. In Section 3, a detailed discussion of our methodology is covered, including the setup of the eye-tracking experiment at BT and the relevant analytical techniques we have applied. Section 4 highlights analytical results, and Section 5 shows our evaluation of the entire study. Finally, we draw some conclusions in Section 6, supported by BT's industrial feedback on the results.
## 1 Introduction
The integration of these components enhances the accuracy and robustness of the IDS, enabling the effective detection of potential intrusion behaviors within the network. In order to tackle the issue of class imbalance, CBF-IDS employs focal loss, which increases the weight of minority classes during the training process, allowing the model to prioritize learning from these classes. The contributions presented in this paper are outlined below:  
* We propose CBF-IDS, an IDS based on the CNN-BiLSTM architecture. By leveraging the strengths of CNN and BiLSTM, CBF-IDS effectively extracts spatial and temporal features from network traffic data, significantly enhancing its classification capability. * In order to tackle the challenge posed by class imbalance, we employ the focal loss function, which assigns higher weights to minority classes, thereby enhancing the model's ability to learn from those specific classes. * We evaluate the performance of CBF-IDS on three datasets: NSL-KDD, UNSW-NB15, and CIC-IDS2017. The findings indicate that CBF-IDS surpasses other models in multi-classification, underscoring its capability to generalize and perform effectively in traditional network environments. The subsequent sections of this paper are organized in the following. In Section 2, we present an overview of the pertinent research in machine learning and deep learning for IDS. Section 3.1 presents an overview of the datasets utilized and outlines the design architecture of CBF-IDS. Section 4 presents a comprehensive analysis of the experimental results obtained from CBF-IDS. Section 5 discusses the research findings of this paper and outlines future work. Section 6 provides a conclusion of the paper.
# FEA-Based Design Procedure for IPMSM and IM for a Hybrid Electric Vehicle
## 1 Introduction
### Contributions and Significance  
The main contribution of this paper includes a thorough exploration of approaches for the design of electrical machines utilizing finite element analysis tools. It integrates electromagnetic and thermal analyses to assess the overload performance and transient temperature variation for IMs and IPMSMs for application in HEVs, which has received limited attention in the literature. While the core concepts presented are known, this study contributes to advancements in the design of electrical machines tailored to specific operational conditions, rendering it of relevance and practical significance. It highlights the trade-offs between size and performance regarding the inclusion of overload capability and temperature consideration. It also includes a comprehensive literature review, elucidating the unique aspects of the proposed approach compared to prior methodologies, as well as a comparative analysis of the performance parameters of two machine designs against well-established commercial counterparts. The paper goes beyond the explanation of the traditional electromagnetic design methods by addressing how different machine types handle the overload conditions and critically analyzing their temperature limitations. The paper clarifies the difference between the torque capability of both machines by consideration of the temperature and overload capability limits. Other contributions include analysis of the impact of the use of deep V-shape PMs in achieving high torque density with low torque ripple and the analysis of the effect of the number of rotor bars on the performance parameters of the IM.
# Recent Advances in Flexible Resistive Random Access Memory
## 5 Conclusions and Challenges  
To sum up, as the next generation of flexible RRAM with the most development potential, the research of flexible RRAM materials has made great progress. However, in order to meet the higher requirements of high flexibility, small size, high durability and low cost, flexible RRAM still faces some important challenges: Firstly, it is urgent to explore the resistance transition mechanism and failure mechanism of flexible RRAM and the three-dimensional configuration of devices (such as vertical cross array and stacked cross array), so as to further guide device performance optimization. Secondly, material cracks are the main cause of device failure under severe bending conditions, so it is urgent to explore materials with better flexibility (liquid materials are also a development direction). Finally, since the practical application environment of flexible devices is usually more complex than the bending conditions in the laboratory, the performance of flexible RRAM under torsion and tensile conditions needs to be emphasized and strengthened. In the research direction, the research on dielectric materials with both stable storage performance and good flexibility, the research on electrode materials with good conductivity, mechanical stability and flexibility and the research on the regulation of electrode/dielectric interface has achieved initial results, but there is still a lack of more in-depth research. Another question is whether the test of flexibility is too ordinary. The test in the laboratory has a very great deal of difference with the actual use, so a more effective testing method needs to be explored. If the above challenges can be well solved, it can be expected that flexible RRAM, as an important component of flexible electronic products, will bring great convenience to people's lives and promote the further development of society.  
**Author Contributions:** Conceptualization, writing--original draft, validation, P.T. and J.C.; formal analysis, T.Q.; resources, X.F.; data curation, M.L.; writing--review and editing, H.N.; visualization, Z.X.; supervision, D.L.; project administration, R.Y.; funding acquisition, J.P. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported by National Natural Science Foundation of China (Grant No. 22090024 and 62174057), Key-Area Research and Development Program of Guangdong Province (No. 2020B010183002), Special Fund for Science and Technology Innovation Strategy of Guangdong Province in 2021 (\"Big Special Project+Task List\") Project (No. 210908174533730), Guangdong Major Project of Basic and Applied Basic Research (No. 2019B030302007), National Natural Science Foundation of China (Grant No. 62074059), the Science Foundation of Yulin Normal University (No. G2020 ZK01) and Ji Hua Laboratory Scientific Research Project (X190221 TF191).  
**Data Availability Statement:** Informed consent was obtained from all subjects involved in the study.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Identification of Terahertz Link Modulation in Atmospheric Weather Conditions
## 3 Simulation and Discussion
### Performance under Different Weather Conditions
It should also be noted that the accuracy of LSTM in rain, fog and haze, and wind weather is close to  
Figure 3: Simulation results by CNN network with a voting enhancement algorithm (CNN enhancement) a 10 GHz baseband signal. (**a–d**) are in clear weather, rain, fog and haze and wind, respectively. (The value of SNR is 13 dB for all the simulations, the value in each grid represents the number of real labels identified to be other label, with 500 labels considered). that in clear weather with the high SNR level, which indicates that the LSTM network has a potential to overcome the degradation caused by adverse weather conditions. Currently, we consider that various environments occur independently, but the actual weather environments may occur simultaneously--for example, strong winds may be accompanied by rainfall. We believe this can lead to more serious identification errors. Therefore, we will carry out more work in different scenarios in the future to better align with the actual situation.
###### Abstract  
This study aims to evaluate five different methodologies reported in the literature for developing fragility curves to assess the seismic performance of RC structures subjected to structural bounding. In this context, displacement-based and curvature-based fragility curves are developed. The use of probabilistic seismic demand models (PSDMs) on the fragility assessment of the bounding risk is further estimated. Linear and bilinear PSDMs are developed, while the validity of the assumptions commonly used to produce a PSDM is examined. Finally, the influence of the PSDMs' assumptions on the derivation of fragilities for the structural bounding effect is identified. The examined bounding cases involve the interaction between adjacent RC structures that have equal story heights (floor-to-floor interaction). Results indicate that the fragility assessment of the RC structure that suffers the bounding effect is not affected by the examined methodologies when the performance level that controls the seismic behavior is exceeded at low levels of IM. Thus, the more vulnerable the structure is due to the bounding effect, the more likely that disparities among the fragility curves of the examined methods are eliminated. The use of a linear PSDM fails to properly describe the local inelastic demands of the structural RC member that suffers the impact effect. The PSDM's assumptions are not always satisfied for the examined engineering demand parameters of this study, and thus may induce errors when fragility curves are developed. Nevertheless, errors induced due to the power law model and the homoscedasticity assumptions of the PSDM can be reduced by using the bilinear regression model.  
RC structure; structural bounding; probabilistic seismic assessment; fragility curves; global and local EDPs; linear and bilinear PSDMs; PSDM's assumptions; nonlinear dynamic analyses; Eurocode 8 +
Footnote †: journal: Applied Sciences
## 4 Results
### Mesh and Model Selection
#### 4.2.3 Velocity Field Analysis  
The jet's shear stress zone's velocity pattern exhibited higher numerical values than experimental data, considering an initial turbulence intensity of 5% at the jet inlet section. When analyzing velocity decay along the jet's centerline, both solvers maintained a coherent jet core over a distance that appeared mesh-independent. Comparisons indicate that the numerical results align more closely with findings from prior experimental studies, although both solvers overestimate velocities relative to experimental data.
## 4 Model Validation
### Comparison of the Pile Foundation of the Slippage Model with the Model Tests
#### 4.2.1 Model Materials  
The sand used in the model test was taken from the Coast of Zhou Shan Island. In this study, a model box with a steel cylinder of 1500 mm diameter and height was used, as shown in Figure 3a. The schematic diagram of the model test can be seen in Figure 3b, which shows the distribution of the upper artificially frozen soil and the lower thawed soil, with the location of the shaker installation and the buried position of the temperature sensor. Two sets of temperature sensors were set at 50 mm intervals along the depth. The inside of the model box was laminated with a circle of wave-absorbing cotton, which can eliminate the effect of reflected waves. The filter layer at the bottom of the model box consists of gravel of different grain sizes.  
The test system consists of a self-made ground-freezing system, a vibration loading unit and a signal acquisition section. The artificial ground-freezing system consists of a one-way refrigeration plate and a DC-2030 refrigeration compressor, as shown in Figure 3c,d. The vibration loading unit consists of an electrodynamic shaker, a HEAS-50 power amplifier and a DF1405 digital synthesized function signal generator, as shown in Figure 3e-g. The signal acquisition section mainly consists of a KD1100 LC acceleration sensor, a KD5201 constant current adapter and a WS-5921U data-acquisition instrument, as shown in Figure 3h-j.  
Figure 2: Verification of the simplified layered model with the existing results (Reprinted/adapted with permission from Refs. [61, 63, 70]. 2020; 2004; 2009, Elsevier; Korean Society of Civil Engineers; Taylor & Francis). (**a**) Four cases of degradation validation; (**b**) comparison with [PERSON] experimental data for validation; (**c**) comparison with [PERSON] numerical simulation data for validation and (**d**) comparison with [PERSON]’s theoretical model.  
After reviewing the modulus of elasticity of various materials, PVC pipe was selected as the material for the model pile. An overview of the model test parameters is listed in Table 1.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multicolumn{1}{c}{Pile} & \(\rho_{b}=1380\) kg/m\({}^{3}\) & \(E_{b}=2.5\times 10^{9}\) Pa & \(H=0.9\) m & \(r=0.04\) m \\ \hline Frozen soil layer & & & & \\ (0.25 m) & & & & \\ Soil layer (0.90 m) & & & & \\ Cap & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Model test parameters of the pile-soil-cap system.  
Figure 3: Schematic diagram of the artificial frozen experimental system for the model pile tests. (**a**) Model box; (**b**) schematic diagram of the model test; (**c**) one-way refrigeration plate; (**d**) DC-2030 refrigeration compressor; (**e**) shaker; (**f**) HEAS-50 power amplifier; (**g**) DF1405 digital; (**h**) KD1100 LC acceleration sensor; (**i**) KD5201 constant current adapter and (**j**) WS-5921U data-acquisition system.
# IoT Helper: A Lightweight and Extensible Framework for Fast-Prototyping IoT Architectures
## 3 System Architecture
### Support Library  
External systems can be seen as _clients_ that require services from the Embedded System--acting as a _server_--through the Message Broker. Clients apps may be implemented by using any high-level language or platform, such as Java Desktop applications, Android or iOS mobile applications or low-level firmware. Software developers need to implement messaging functionalities as described in Section 3.1 to and from the Message Broker.  
To ease the development of such clients, we designed and implemented a support library in Java and Objective-C. This library offers a high-level interface to communicate with the framework. The Application Level Interface (API) consists in three main components: ICIient, Command and PinValue. The UML class diagram [26] is reported in Figure 3.  
The Command represents the action that the client wants to execute. A command is identified by a type, which can be READ, REPEATED_READ, WRITE or TIMED_WRITE, and a list of PinValue. In the case of a read request, each PinValue contains only the identifier of the sensor, while the value will be populated after executing the command. For a write command, the client needs to specify the identifier of the actuator and its new value. The communication with the Message Broker is managed by the ICIient interface that has several implementations, one for each supported Message Broker. In the current version of the library, we support MQTT and two SaaS cloud solutions, PubNub and Google Cloud Pub/Sub. Using this library, clients will not have to create messages and parse responses, and the integration with the embedded system will be simpler. In addition, the ICIient hides the asynchronous communication exposing a synchronous interface, which is usually easier to handle. When the client performs the execute method, a request message with a new _token_ is sent to the appropriate topic and the execution flow is interrupted until a message for that token is published on the response topic.
# Artificial-Intelligence-Based Charger Deployment in Wireless Reshargeable Sensor Networks
## 2 Related Works
### Wireless Charging Planning  
Some scholars mapped the charging problem as a Hamilton cycle and let the whole environment be divided into multiple clusters. They also proposed a greedy-based 26 algorithm to find a shortest path for charging. However, this method did not consider that some sensors have too little energy so that they will run out of energy before charging vehicles arrive [26]. In [27], the authors took Washington as an example. They tried to detect the number of pedestrians from infrared images and then figured out which area of pedestrians is the most intensive. The major goal of this work was to improve the survival rate of terminal devices. However, statistics-based methods usually do not have good environmental adaptability. In [28], the authors used unmanned aerial vehicles (UAVs) for charging. They can be used in the extremely rough terrain which cannot be traversed by self-propelled vehicles. The authors also divided the sensors into multiple clusters. The data of sensors were transmitted when the UAV was arriving for charging. Their proposed one-side matching algorithm considers the remaining power and distance of UAV flight to calculate the optimal charge-priority order. In addition, some scholars considered the collision avoidance [29], minimum number of disjoint shortest trees [30] and multiple self-propelled vehicles [31] to design a better charging plan. Most works adopted intermittent charging. This means that the charging process only begins when the self-propelled vehicle has arrived, and then it will stay in there until the termination condition is met. However, sensors will sense current as long as the self-propelled vehicle passes by them. In [32], the authors proposed a real-time charging method to extend network lifetime. The authors proposed a spatial-temporal discretization method in which each time block is independently assigned based on travel speed and the distance from the sensors. In other words, this method can optimize where to go to charge the sensors. For the indoor scenario, the authors of [19] proposed a greedy-based method to quickly deploy chargers. In [33], the authors adopted the concept of a center of gravity to find the best charging position and proposed a charging-schedule algorithm to increase the remaining-use durations of sensor nodes. In [34], the authors proposed a particle swarm charger-deployment algorithm that utilizes the local optimal result and the global optimal result to adjust locations and antenna orientations of chargers.
## 3 Methodology  
In this study, we implemented a TL strategy by adapting well-known image recognition models (AlexNet, GoogLeNet, SqueezeNet, ResNet-18, and ResNet-50) and speaker embedding models (d-vector, x-vector, and r-vector) for SER. Building on our previous work [17], we further refined the architecture of the x-/r-vector models to enhance their emotion recognition capabilities. The original speaker embedding systems serve as baselines to evaluate the impact of proposed improvements on capturing and classifying emotional nuances in speech.