esa-sceva/satcom-chunk-collection huggingface dataset:
# Possibilities of Evaluating the Effectiveness of Noise Barriers in Slovakia
## 1 Introduction
In the territory of the Slovak Republic, the construction of noise barriers was developed in the late 1980s and early 1990s of the 20 th century, when traffic, especially road traffic, increased accompanied with increased noise emissions to the surrounding residential areas. There was also a change in political and social views on the protection of the environment and the protection of citizens' rights [13]. Along railway lines, noise barriers began to be built in the first half of the 1990s, in connection with the modernization of railways. There was a significant increase after 2007, when the aforementioned Decree of the Government of the Slovak Republic was adopted [10]. Experts recommended prioritizing noise-mitigating measures at source, as they are more cost effective. Nevertheless, according to the latest figures [14], a total of EUR 150-200 million is being spent in Europe on the construction of noise barriers. Noise barriers are an effective element in reducing noise in densely populated urban areas [15]. However, are these barriers the correct height, shape, material design, and construction? For better design of noise barriers and to identify sufficient protection of the population against noise generated by road traffic, it is necessary to determine their effectiveness by the so-called insertion loss of the barrier. Their effectiveness is determined by the direct and indirect method and the Adrienne method. This paper presents the individual methods, measurements by the indirect method, verification of the barrier by our own simulation method, and measurement by the Adrienne method for assessment of the noise barriers' effectiveness. This article will also address methods used for evaluating the effectiveness of noise barriers on roads in Slovakia. The main objectives solved within are as follows:  
* Possibilities of evaluating of noise barriers' effectiveness,
* Advantages and disadvantages of the individual methods of evaluating noise barriers' acoustic characteristics;
* Measurement methods of acoustic performance and their realization on real noise barriers on selected sections of highways; and
* Discussion of the measured results from individual methods and their applicability.
## 3 Results and Discussion
### Neural Network Complexity  
In Table 3, we present the numbers of parameters, FLOPs, and memory sizes of the models. The FLOPs and memory size were calculated based on the input size of \(3\times 256\times 256\) using the sliding window method. There were seven sequence images for CLSTM, U-Net-LSTM, and BDULSTM. According to our benchmarks, BDULSTM is a moderately sized model, with 50.82 M parameters and 32.87 GFLOPs. For comparison, U-Net-LSTM has 51.90 M parameters and 38.47 GFLOPs.  
Although more complex than both the basic CLSTM and U-Net, BDULSTM has lower model complexity than U-Net-LSTM and exhibited better performance on our benchmarks. Additionally, the memory size of BDULSTM is 409.50 M, while that of U-Net-LSTM is 442.50 M. Therefore, BDULSTM requires less memory than U-Net-LSTM to process sequence images.
# Path Planning under Force Control in Robotic Polishing of the Complex Curved Surfaces
## 2 The Proposed Method  
The key to robotic polishing is the tool path. Ideally, it shall have the minimum path length, the best coverage of the polishing surface and the uniform surface quality. A top-down approach is developed for tool path planning. Figure 1 shows the setup for the robotic polishing of the eyeglass frames, which includes an articulated robot with a supporting fixture to hold the workpiece and a force feedback system to control the polishing force of the tool through a variable speed motor.  
The flow chart of the proposed robotic polishing method for the complex curve surfaces is presented in Figure 2. It consists of two major stages (workstation building and path planning). In the workstation building stage, polishing tool selection, decision for using a tool or workpiece as the end effector, and force controlling strategy are determined because these decisions affect the tool path planning. Path planning can be further divided into three stages. First is surface division, in which the surface to be polished is divided into several regions. For each region, the limits of the robot joints and surface normal vector are considered to ensure continued orientation. Second is tool path generation, in which each surface region is assigned a tool path with specific pattern and polishing parameters. The quality of the polishing surface and productivity are the major considerations here. Finally, the tool path stitching, in which the tool paths in different regions are stitched together. The major considerations include the shortest connecting routes and jerk avoidance. These parts are detailed below.  
Figure 1: The setup for the robotic polishing of the eyeglass frames.  
Figure 2: The flow chart of the proposed method for polishing the complex curved structures.
# Hybrid Impedance-Admittance Control for Upper Limb Exoskeleton using Electromyography
## 2 Background
### Electromyography
#### 2.2.2 Characteristics of the Electromyographic Signal  
The properties of the electrical signal generated by the contraction vary according to the muscle [12; 13]. Fast contraction muscles reach maximum tension in one-seventh of the time of a contraction muscle [12; 27]. The myoelectric signal occurs within the range of 0-1000 Hz, with most of the signal of interest being between 25 and 500 Hz [12; 13; 27]. Electromyography devices use low-pass and high-pass filters to ensure the capture of the correct frequencies of the electrical signals generated by the muscles. These filters remove noise and interference produced by the measuring device [12; 13; 27].  
The electromyographic signal can be used in three ways: raw, rectified, and integrated. Raw EMG performs the pure reading of the signal and is typically used in the diagnosis of diseases that affect the muscles or in classifications that consider the frequency of the signal [27]. Rectified EMG converts the raw signal to a single polarity signal, which is typically positive to ensure that the signal does not average to zero. This approach is used in the same applications as the raw EMG. [12]. Finally, the integrated EMG performs the peak-to-peak linearization of the wave and is used to measure muscle effort. This approach is also used in systems that process EMG signals with low computational cost [27].
## 4 Discussion  
We conducted a comparative experiment between seven baseline algorithms and our methodology using two datasets from the movie domain, which vary in size and characteristics. As shown in Table 4, our model does not always outperform the others, but it provides greater explainability through the use of user profiles.  
Table 3 presents a list of properties found in the frequent subgraphs, helping to understand the properties of movies that people are most interested in. These properties are the constituent elements of user profiles, and each user profile contributes to enhancing the explainability of each recommendation. Additionally, the fitting capability of the deep neural network model enables our method to demonstrate satisfactory performance.  
Rather than adapting and testing various neural network structures, we concentrated on demonstrating that user profiling through frequent subgraphs provides explanatory recommendations with an adequate performance.  
To better understand the cause of performance decline on the ml-1m dataset, we attempted to discern how the characteristics of the data affect our algorithm. Through experimentation, we concluded that sparsity plays a significant role; when there is a high overlap in the items selected by users, the differences between user profiles diminish, which, in turn, leads to lower performance. In other words, the algorithm performs well when users' choices or preferences are relatively diverse.
# Smart Warehouse Management System: Architecture, Real-Time Implementation and Prototype Design
## 8 Results and Discussion
### Key Performance Indicators
#### 8.1.3 Power Dissipation  
As the number of nodes increases in a system, the power intake increases as well. With the use of MQTT, we made sure that the power dissipation was kept to a minimum as compared to HTTP. MQTT uses power only during transmission, whereas HTTP remains awake after the initial handshake. A comparison of the power dissipation of MQTT and HTTP in Figure 13 shows that at the beginning, MQTT used up some power to connect and set up; however, once connected, it had a very minimum power dissipation for every subsequent message, as compared to HTTP. On the contrary, HTTP firsts sets up the three-way handshake, then keeps using power continuously, regardless of the message transmissions. This, overall, makes MQTT an efficient option for long-term, lightweight data transmissions with devices that are portable and battery powered.
# A Bidirectional Trust Model for Service Delegation in Social Internet of Things
## 2 System Overview and Problem Statement
### Step 3: The SR Delegates the Task to the SP  
After receiving several responses, the SR \(u_{i}\) will consider the factors of trust and utility to make a decision of service delegation. Similar to the process of trust evaluation of the SR from the viewpoint of the SP in step 2, the trust of the SP \(v_{j}\) from the viewpoint of the SR \(u_{j}\) is formulated as  
\[\overrightarrow{T}_{v_{j}\gets u_{i}}(\varphi)=f_{ct}(\overrightarrow{T }_{v_{j}\gets u_{i}}^{d}(\varphi),\{\overrightarrow{T}_{v_{j}\gets k _{k}}^{rec}(\varphi)\}_{k=1,2,\ldots}), \tag{3}\]where \(s_{k}\) denotes the intermediate objects which have some interactions with the SP \(v_{j}\). Based on the trust analysis, the SR will determine the delegated SP by solving the following formulation:  
\[\begin{split}& DSP=\operatorname*{arg\,max}_{v_{j}}\ f_{tu}(\overrightarrow{T}_{v_{j}\gets u_{i}}( \varphi),\psi_{v_{j}}(\varphi)),\\ & s.t.\ \ \ g(\overrightarrow{T}_{v_{j}\gets u_{i}}( \varphi))\geq th_{u}(\varphi)\end{split} \tag{4}\]  
where \(f_{tu}\) is the delegation function that calculates the integrated index for service delegation. \(th_{u}(\varphi)\) is a trust threshold set by \(u_{i}\) for the task \(\varphi\).  
Step 4: The Delegated SP Performs the Task and Submits the Result, and Then the SR and SP Will Mutually Comment Each Other  
After receiving the delegation message from the SR, the delegated SP (we assume \(v_{j}\)) will perform the task and submit the result. After that, the SR will evaluate the result according to the accuracy, real-time, etc., of the task performance to decide the success or failure of the task. The SR's evaluation of the task is denoted by \(\mathrm{Y}^{t_{\varphi}}_{v_{j}\gets u_{i}}(\varphi)\), where \(t_{\varphi}\) is the occurred time of the task \(\varphi\). If the SR is satisfied according to the SP's performance, the \(\mathrm{Y}^{t_{\varphi}}_{v_{j}\gets u_{i}}(\varphi)\) will be set \(1\), and it will be set \(-1\) if the SR is unsatisfied. Similarly, the SP will also evaluate the SR's behavior in the process of the task, which is denoted by \(\mathrm{Y}^{t_{\varphi}}_{u_{i}\gets v_{j}}(\varphi)\). If the SP is satisfied, then the \(\mathrm{Y}^{t_{\varphi}}_{u_{i}\gets v_{j}}(\varphi)\) will be set \(1\), and it will be set \(-1\) if the SP feels unsatisfied.
# An Efficient GNSS Coordinate Recognition Algorithm for Epidemic Management
## 5 Simulated Environment and Demonstration
### Simulated Environment  
The simulated geographic area was mainly the island of Taiwan, which is located between 120 and 122 degrees East for the longitude and 22 and 25 degrees North for the latitude. It covers an area of 35,808 km\({}^{2}\) and has a population of 23.7 million inhabitants.  
Figure 8 presents the simulated environment. Figure 8a shows the distribution of residents per kilometer in villages in 2019 [32]. The targeted points for the simulation were based on geographical points acquired from a famous social network service platform, with a total of 1,112,188 points [24]. Figure 8b presents the distribution of the targeted points, which included 10,000 points that were randomly selected from all targeted points. Through a comparison of Figure 8a,b, The area currently contains six municipalities, of which three--Taipei City, Taichung City, and Kaohsiung City--were selected as the targeted areas. Taipei City is Taiwan's political, economic, educational, and cultural center, and it  
Figure 6: Partitioning a rectangle into a set of squares.  
Figure 7: The distribution of the targeted points in Taipei City.  
is one of the major hubs in East Asia. Taichung City, which is located in central Taiwan, plays an essential role in Taiwan's economic development and transportation systems. Kaohsiung City is a special municipality in southern Taiwan, and it is Taiwan's third most populous city and the largest city in southern Taiwan. For brevity, Taipei City, Taichung City, and Kaohsiung City are called City 1, City 2, and City 3, respectively.
# Review of CMOS Integrated Circuit Technologies for High-Speed Photo-Detection
## 5 Bandwidth Extension Techniques  
In the CMOS front-end for photodetection, there are many parasitic capacitances that limit the circuit bandwidth, such as the input capacitance of PD, parasitic capacitances of CMOS devices, and output loading of TIAs. Therefore, as the required communication bandwidth for optical links increases, CMOS circuits have become a bottleneck for achieving such high bandwidth. Several circuit techniques for bandwidth extension of TIAs and optical receivers have been presented in the literature [80; 85; 95; 96; 97; 98; 99; 100]. The techniques are classified into two categories: an inductive peaking technique and an equalization technique. In this section, a brief summary and categorization of various bandwidth extension techniques are presented.
## 3 Memristive Analog Design  
Memristor-based analog circuits have gained attention in recent years due to their potential for low-power and high-density integration. These circuits offer advantages over traditional digital potentiometers, such as improved linearity and faster response times. High-voltage pulses are used to control the memristor resistance and can be easily adjusted to achieve precise analog signal manipulation. Their ability to store information in resistance states makes them suitable for applications in various functions, such as amplification, filtering, and signal processing. Also, they offer advantages such as low power consumption, high speed, and a compact size compared to traditional analog circuits. Memristive analog circuits have the potential to achieve higher levels of integration and density, making them suitable for applications requiring complex circuitry in a limited space. Furthermore, they maintain their state even in the absence of power, enabling non-volatile memory storage. This feature makes them ideal for applications that require data persistence and quick access to stored information. Additionally, memristive analog design offers flexibility and adaptability in various electronic systems through easy reconfiguration and programming.  
This section explores the analog memristive circuits, including programmable circuits, DACs, and RF circuits, among others, that have been reported in the literature. These circuits have demonstrated impressive performance and energy efficiency, positioning them as a compelling choice for a wide range of electronic applications. Furthermore, the potential impact of these circuits on the field of electronics is significant, attracting significant interest and research.
## 4 Conclusions  
This investigation has demonstrated a novel approach to determine the proper strategy for synthesizing high thermally resistant modified Mt, with enlarged interlayer spacing. The effects of various strategies combining acid activation, ion exchange, and silylation, on the modification of Mt, have been studied. After the acid treatments, increases in the BET surface area and BJH pore volume, and reductions in the amount of Na+, were observed for the sample. The amount of chemical grafting of the \(\gamma\)-MPS was increased with the acid treatment, whereas the amount of intercalation of the TTPC surfactant was decreased. According to the XRD and TEM analysis, a significant interlayer spacing enhancement was observed in the TTPC surfactant-treated samples. On the contrary, no significant changes were obtained when the silylation reaction was performed on the samples. The results of FTIR and XRF revealed that the preintercalation or silylation modification of the Mt had a certain hindrance effect on its subsequent modification. The higher thermally resistant modified OMt that was found for samples that were treated by three different treatments, indicates that both the samples have the potential to act as effective nanofillers in the polymer matrix. The PS nanocomposites using triple-modified Mt showed much higher thermally resistant stability than pure PS and PS nanocomposites reinforced by double-modified samples. The \(T_{.5\%}\) and \(T_{\text{max}}\) of the PS nanocomposites using H-P-Si-Mt were noticeably enhanced to 386 \({}^{\circ}\)C and 435 \({}^{\circ}\)C (increased by 27 \({}^{\circ}\)C and 32 \({}^{\circ}\)C), respectively, compared with the neat PS. This was mainly attributed to the exfoliated two-dimensional layers with large surface areas, which increased the dispersion and interfacial interaction in the polymer matrix, resulting in the formation of a more complex tortuous pathway, to constraint the diffusion of volatile decomposition products. This approach of modification for Mt opened opportunities for the design of polymer/clay nanocomposites with enhanced thermal properties, which was an interesting result for applications in lubricating materials in oil and gas drilling engineering.  
Conceptualization, Y.K.; methodology, J.L.; validation, X.H.; investigation, C.Y.; data curation, S.L.; writing--original draft preparation, C.Y.; writing--review and editing, Y.K. All authors have read and agreed to the published version of the manuscript. This research was funded by the China Postdoctoral Science Foundation (grant No. 2020M670307), and the National Major Project of China (grant No. 2017 ZX05009-003). Not applicable. Not applicable. Not applicable. Not applicable. Not applicable. Not applicable.  
The authors declare no conflict of interest.
## 2 Reflection Power Estimation Using Eigenbeam Spatial Correlation Model
### Methodology
The elements in \(\mathbf{\Lambda}(t,k|\mathbf{y}_{o})\) and \(\mathbf{B}(k,\mathbf{y}_{o})\) can be generated from the \(\alpha_{nm}(t,k|\mathbf{y}_{o})\) coefficients and source direction information, respectively. Now, we can solve (10) to estimate \(\mathbf{\Omega}(t,k|\mathbf{y}_{o})\) by  
\[\mathbf{\hat{\Omega}}(t,k|\mathbf{y}_{o})=\mathbf{B}^{\dagger}(k,\mathbf{y}_{o})\mathbf{\Lambda}(t,k|\mathbf{y}_{o}) \tag{14}\]  
where \([\cdot]\) and \([\cdot]^{\dagger}\) indicate estimated values and pseudo-inversion operator, respectively. While solving (14), the order of \(\gamma_{nu}(t,k|\mathbf{y}_{o})\) in \(\mathbf{\hat{\Omega}}(t,k|\mathbf{y}_{o})\) is truncated to \(V\leq\left\lfloor\sqrt{(N+1)^{4}-1}\right\rfloor\), where \(\left\lfloor\cdot\right\rfloor\) indicate flooring operation, to avoid an underdetermined system [34]. Once the \(\gamma_{nu}(t,k|\mathbf{y}_{o})\) coefficients are extracted from \(\mathbf{\hat{\Omega}}(t,k|\mathbf{y}_{o})\), we can generate the reflection power using Equation (6) for different incoming directions \(\hat{\mathbf{y}}\) and time-frequency bins. From \(P_{R}(t,k,\hat{\mathbf{y}}|\mathbf{y}_{o})\), we can estimate the total reflected power in any time-frequency bin as  
\[P_{T}(t,k|\mathbf{y}_{o})=\int_{\hat{\mathbf{g}}}P_{R}(t,k,\hat{\mathbf{y}}|\mathbf{y}_{o})d \hat{\mathbf{y}}. \tag{15}\]  
Substituting (6) in (15) and using the symmetrical property of spherical harmonics [35]\(P_{T}(t,k|\mathbf{y}_{o})=\gamma_{00}(t,k|\mathbf{y}_{o})\). We can now use \(P_{R}(t,k,\hat{\mathbf{y}}|\mathbf{y}_{o})\) and \(P_{T}(t,k|\mathbf{y}_{o})\) to analyze the reflection power variations with time, frequency, and direction.
## 3 Results and Discussions  
### Influence Mechanism of Environmental Parameters  
During CCT, the losses are often caused by the inability to perceive the quality changes of perishable food in real-time. The quality changes of strawberries are impacted by the multiple microenvironmental parameters reacting together (Figure 6). This paper selected four environmental parameters, which had the most important impact on strawberry quality.  
Temperature  
The quality of post-harvest fruit would continue to change with a series of physiological activities such as respiration, until the fruit decayed at the end. Temperature is one of the most important environmental factors [22]. The temperature fluctuations in refrigerated compartments lead to perishable goods losses. Therefore, it is important to implement real-time temperature monitoring [23].
## 2 Materials and Methods
### Neural Network Model
#### 2.5.4 Lstm  
LSTM stands for Long Short-Term Memory, which is a type of recurrent neural network [25; 26]. It was designed to overcome the vanishing gradient problem in traditional RNNs and allow for the processing of long-term dependencies. LSTMs use a series of gates, including an input gate, a forget gate, and an output gate, to selectively allow information to flow through the network and control the memory stored in the hidden state. This enables LSTMs to selectively remember or forget information from previous time steps as needed, making them well-suited for tasks such as language modeling, speech recognition, and handwriting recognition. The LSTM utilized in this article consists of 16 hidden layers and 2 LSTM layers. The purpose of the hidden layers is to introduce non-linear mappings, thereby enhancing the expressive capacity of the network. LSTM, a special type of recurrent neural network (RNN) architecture, addresses the issue of vanishing and exploding gradients encountered by traditional RNNs by incorporating gate mechanisms. The LSTM layer exhibits memory capabilities when processing sequential data, enabling effective handling of long-term dependencies.
## 3 Results and Discussion
### Analysis of Infrared Spectra from Control and Exposed Cells
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**0 Gy** & **Assignment** & **0.5 Gy** & **2 Gy** & **4 Gy** \\ \hline Peak & & Peak & Peak & Peak \\ (cm\({}^{-1}\)) & & (cm\({}^{-1}\)) & (cm\({}^{-1}\)) & (cm\({}^{-1}\)) \\
3493 & c & 3490 (\(-\)3) & 3492 (\(-\)1) & 3493 \\
3418 & c & 3411 (\(-\)7) & 3417 (\(-\)1) & 3421 (\(+\)3) \\
3291 & p, c & 3291 & 3295 (\(+\)4) & \\
3173 & p & 3179 (\(+\)6) & 3178 (\(+\)5) & 3186 (\(+\)13) \\
3071 & p, c & 3078 (\(+\)7) & 3081 (\(+\)10) & 3071 \\
2959 & p, l & 2960 (\(+\)1) & 2960 (\(+\)1) & 2960 (\(+\)1) \\
2924 & l & 2924 & 2924 & 2923 (\(-\)1) \\
2889 & p, l & 2880 (\(-\)9) & 2880 (\(-\)9) & 2893 (\(+\)4) \\
2852 & l & 2855 (\(+\)3) & 2858 (\(+\)6) & 2859 (\(+\)7) \\
1643 & p & 1643 & 1645 (\(+\)2) & 1644 (\(+\)1) \\
1534 & p & 1534 & 1534 & 1535 (\(+\)1) \\
1448 & p, l & 1448 & 1451 (\(+\)3) & 1451 (\(+\)3) \\
1394 & P & 1394 & 1395 (\(+\)1) & 1396 (\(+\)2) \\ \hline \end{tabular}
\end{table} 
Table 3: Average FTIR peaks position for control and samples treated with different doses fixed immediately after irradiation. The shifts in respect of the non-irradiated sample, in terms of units of wavenumber are indicated in brackets (bold values stand for shifts greater than the spectral resolution of the instrument 4 cm\({}^{-1}\)). Abbreviations: p = proteins, l = lipids, c = carbohydrates.