esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Experiment Results
### Experimental Results
In addition, this model achieved the highest F1-score (0.78801), which is the harmonic mean of precision and recall. This result suggests that the model balances precision and recall effectively. Finally, the InceptionV4 model with the defect-adaptive hierarchical structure and customized loss function achieved the highest accuracy of 0.73214, reflecting the best overall performance in terms of correct predictions across the dataset. As shown in Figure 13, For the **no_lens** class, almost all models showed good results. However, for the **etc** class, where defects often occupy the entire image, EfficientNet performed the best. In the **etc** class, features occupy the entire image, which differs from typical manufacturing scenarios. In manufacturing, defects typically appear as small anomalies against a consistent background, whereas in the **etc** class, the background itself
## 4 Experiments and Analysis
### Experiment Setting
#### 4.2.2 Hyperparameters Setting for DDPG  
The setting of DDPG is described below. There are two hidden layers in the actor net with 300 neurons in each layer. For the critic net, there are 200 neurons and 150 neurons for the two hidden layers. The learning rates of the actor net and the critic net are set to 0.002 and 0.01, respectively. These nets are trained for 200 epochs with a discount factor \(\gamma\) of 0.95. The initialized Gaussian noise is 0.5, and the noise's decay factor is 0.96. The replay buffer's capacity is set to 2000, and the size of mini-batch is set to 128.
## 2 Materials and Methods  
The depth in the research area is 30 m; the floor is sand; distance to the shore is 1 nautical mile. Approximately 2 nautical miles away from the research area there is an anchorage and water border of the outer aquatic area of the port of Vladivostok; additionally, there is a route that is used for the entrance and exit of oceanic vessels in and out of the port. The given area is characterized by high shipping intensity; on average, vessels pass through this route every two hours.  
The research was conducted in September-October 2014 in conditions of dry and calm weather; the mean wave height was 0.5 m. The distance from the research area to the nearby anchored vessels at that time was about 3 nautical miles. The current velocity did not exceed 0.1 m/s. The omnidirectional piezoceramic spherical hydrophone was 50 mm in diameter, with medium sensitivity of 180 \(\upmu\)V/Pa within the frequency range of 0.03-4 kHz (constructive elements are considered); it was mounted to the drift buoy with flexible suspension and was used for the signal reception. Submersion depth of the hydrophone was 10 m. Signals received through the hydrophone were transferred to the boat with a water displacement of 3 metric tons via cable with attached floaters; the boat was drifting along with the buoy. The regime of silence was maintained onboard during the measurements; the equipment was powered by accumulator batteries.  
A Bruel & Kjaer Charge Amplifier Type 2635 (Bruel & Kjaer, Naerum, Denmark) with input impedance of 1 Gohm was used as a hydrophone preamplifier. High-grade 24-bit external sound card E-MU 0404 USB2 (Creative Technology Ltd, Jurong East, Singapore) was used for signal sampling; the sampling frequency (fs) was 8 kHz. The digitized signals were recorded on a computer hard drive as *.wav files and then computer-processed in laboratory conditions. Some spectral and statistical characteristics of the sea noise in the research area were described in [5; 6].  
In order to reduce the influence of low-frequency flow noise and noise with frequency components that exceed the Nyquist frequency (4 kHz in the given case) prior to further processing, signals were filtered by the 1024 th-order finite-impulse-response filter with frequency bandwidth 30-3300 Hz.
## 3 Proposed Two-Way Cooperative CF Approaches
### Pearson Correlation-Based Score  
In (1) and (2), \(k_{a}=1/\sum\limits_{i=1}^{n}|w(a,i)|\) and \(k_{b}=1/\sum\limits_{j=1}^{m}|w(b,j)|\) are respectively multiplied to the sums of the correlations to consider the proportions of the contributions. Then, the Pearson correlation-based score for two-way cooperative CF is defined as a weighted mean of \(P_{aj^{\prime}}\) and \(P_{bi^{\prime}}\) as follows.  
\[P_{P(P_{aj^{\prime}},P_{bi^{\prime}})}=P_{aj^{\prime}}\,\frac{\sum_{i=1}^{n}|w( a,i)|}{\sum_{i=1}^{n}|w(a,i)|+\sum_{j=1}^{m}|w(b,j)|}+P_{bi^{\prime}}\frac{\sum_{j=1}^{m} \left|w(b,j)\right|}{\sum_{i=1}^{n}|w(a,i)|+\sum_{j=1}^{m}|w(b,j)|} \tag{8}\]  
The first weight for \(P_{aj^{\prime}}\), \(\sum\limits_{i=1}^{n}|w(a,i)|/(\sum\limits_{i=1}^{n}|w(a,i)|+\sum\limits_{j=1 }^{m}\left|w(b,j)\right|)\) is the proportion of the sum of the absolute values of the Pearson correlations between an active user \(a\) and an existing user \(i\), whereas the second weight for \(P_{bi^{\prime}}\sum\limits_{j=1}^{m}\left|w(b,j)\right|/\left(\sum\limits_{i =1}^{n}|w(a,i)|+\sum\limits_{j=1}^{m}|w(b,j)|\right)\) is the proportion of the sum of the absolute values of the Pearson correlations reveals the importance of the prediction, the two proportions reasonably assign the importance of the prediction to the two predictions, \(P_{aj^{\prime}}\) and \(P_{bi^{\prime}}\).  
For the extreme high-dimensional cold-start problem, where either the row of an active user or the column of an active item in the market basket data are all zeros, we propose that the corresponding Pearson correlations are considered as zeros because they cannot be calculated, and there are low correlations between the two variables. Then, the weighted mean can be reasonably calculated because both \(P_{aj^{\prime}}\) and \(P_{bi^{\prime}}\), the two predictions obtained by the user-based CF and by the item-based CF, become available.
# Self-Organized Proactive Routing Protocol for Non-Uniformly Deployed Underwater Networks
## Related Work
### Opportunistic Protocols  
Energy-efficient opportunistic routing technology (EFFORT) [15] uses opportunistic end-to-end cost (OEC) to reduce the number of candidate nodes from source to destination. This way, the network lifetime increases. The OEC cost is determined based on a candidate node's residual energy and link reliability.  
Energy-efficient and obstacle-avoiding routing (EOAR) [16] uses fuzzy logic to select the forwarding node. The selection is made based on residual energy, the angle between the two nodes, and the propagation delay. Packets are forwarded based on priority to avoid the collisions. The propagation delay is calculated as the time difference between the local current time of the node and the time-stamp included in the received packet. This method requires time synchronization between the nodes, which is a challenging task for UWSNs due to the varying propagation delay and some degree of mobility.  
GDGOR-IA and GRMC-SM [17] use the location information of the nodes to form the routing path, which is established when the data are to be forwarded, thus increasing the routing delay. The data forwarding uses the greedy approach. The network is divided in logical cubes and a set of nodes is selected in each cube to forward the data packet. PICS and PRCS [18] use depth information and ToA to calculate the position of the sender and distance between the nodes. PICS uses two hops information to select the routing path, whereas PRCS uses only one hop information. In order to select the candidate nodes to forward packets, a new metric named EEPA [18] (enhanced expected packet advance) is applied, which considers the channel quality and path correlation between two neighbors.  
The shortcomings of the protocols discussed above are listed as below:  
1. In location-based routing protocols: 1. The sensor nodes determine their position with respect to the GW, which in turn determines its position via GNSS. Due to the varying speed of acoustic waves and the mobility of the nodes, the probability of error in position determination is quite high; 2. The position determination by the depth sensors increases the power consumption and cost of the sensor nodes;
2. Time synchronization is required;
3. Additional devices like a depth sensor and array of antennas (for the angle of arrival method [1]) are required;
4. Centralized routing path formation control;
5. The required computational processing delay and power are high;
6. The routing protocols are reactive.  
In this paper, we designed a routing protocol which addresses all these shortcomings. Our proposed proactive protocol requires no location information, no time synchronization, and no additional devices, and uses less computational power.
## 3 Bias Compensation Estimator for Localization in 3D Space
### Bias Compensation Localization in 2D Space
\right] \mathbf{v} \tag{27}\] \[=\frac{\gamma-\gamma_{\min}}{n}\sum\limits_{i=1}^{n}(v_{1}^{2}+2v_ {1}v_{3}x_{s_{i}}+v_{2}^{2}+2v_{2}v_{3}y_{s_{i}}+v_{3}^{2}x_{s_{i}}^{2}+v_{3}^ {2}y_{s_{i}}^{2})\] \[=(\gamma-\gamma_{\min})((v_{1}+\frac{v_{3}}{n}\sum\limits_{i=1}^{ n}x_{s_{i}})^{2}+(v_{2}+\frac{v_{3}}{n}\sum\limits_{i=1}^{n}y_{s_{i}})^{2}\] \[\quad+\frac{v_{3}^{2}}{2n^{2}}\sum\limits_{i=1}^{n}\sum\limits_{j =1}^{n}(x_{s_{i}}-x_{s_{j}})^{2}+\frac{v_{3}^{2}}{2n^{2}}\sum\limits_{i=1}^{n} \sum\limits_{j=1}^{n}(y_{s_{i}}-y_{s_{j}})^{2})>0,\]  
when \(\gamma<\gamma_{\min}\), the first term \(\mathbf{v}^{{}^{\prime}}P(\gamma_{\min})\mathbf{v}\) in (26) is no less than 0. This makes \(\mathbf{v}^{{}^{\prime}}P(\gamma)\mathbf{v}\) always greater than 0. Hence, the minimum \(\gamma\) that leads to \(\mathbf{v}^{{}^{\prime}}P(\gamma)\mathbf{v}=0\) or \(\det(P(\gamma))=0\) satisfies \(\gamma=\gamma_{\min}\) when \(\mathbf{v}=\beta\big{[}x_{t}\quad y_{t}\quad-1\big{]}^{\prime}\). It is worthwhile to point out that \(\gamma_{\min}\) can be found by getting the minimum root of the third-order polynomial function \(\det(P(\gamma))=0\). To sum up, the 2D positioning results with bias compensation can be obtained, as  
**Theorem 1**. : \[\mathbf{\hat{t}_{bc}}=\left(\frac{1}{n}\mathbf{A}_{n}^{{}^{\prime}}\mathbf{A }_{n}- \begin{bmatrix}\gamma_{\min}&0\\ 0&\gamma_{\min}\end{bmatrix} \right)^{-1}*\left(\frac{1}{n}\mathbf{A}_{n}^{{}^{ \prime}}\mathbf{B}_{n}-\frac{\gamma_{\min}}{n}\sum\limits_{i=1}^{n} \begin{bmatrix} x_{s_{i}}\\ y_{s_{i}}\end{bmatrix} \right)\] (28)  
_converges to \(t\) in probability as \(n\to\infty\) when \(\mathbb{E}(cos2e_{i})\
eq 0\)._  
**Proof of Theorem 1. ** As \(n\to\infty\),  
\[\frac{1}{n}\mathbf{A}_{n}^{{}^{\prime}}\mathbf{A}_{n}- \begin{bmatrix} \gamma_{\min}&0\\ 0&\gamma_{\min}\end{bmatrix} =\frac{\mathbb{E}(\cos(2e_{i}))}{n}\sum_{i=1}^{n} \bigg{(} \begin{bmatrix}\sin\phi_{i}\\ -\cos\phi_{i}\end{bmatrix}\begin{bmatrix}\sin\phi_{i}\\ -\cos\phi_{i}\end{bmatrix} ^{{}^{\prime}}\bigg{)}, \tag{29}\] \[\frac{1}{n}\mathbf{A}_{n}^{{}^{\prime}}\mathbf{B}_{n}-\frac{\gamma _{\min}}{n}\sum_{i=1}^{n} \begin{bmatrix}x_{s_{i}}\\ y_{s_{i}}\end{bmatrix} =\frac{\mathbb{E}(\cos(2e_{i}))}{n}\sum_{i=1}^{n}\bigg{(} \begin{bmatrix}\sin\phi_{i}\\ -\cos\phi_{i}\end{bmatrix}\begin{bmatrix}\sin\phi_{i}\\ -\cos\phi_{i}\end{bmatrix} ^{{}^{\prime}}\bigg{)} \begin{bmatrix}x_{t}\\ y_{t}\end{bmatrix} . \tag{30}\]  
From (29) and (30), Theorem 1 stands when \(\mathbb{E}(\cos 2e_{i})\
eq 0\). \(\square\)
# ICN-Based Enhanced Content Delivery for CDN
## 5 Simulation Study
### Result Analysis  
#### 5.2.1 Enhancement to Performance  
In this experiment, we attempt to evaluate the performance of our proposed design compared with conventional CDN. We use the Abilene topology for analysis and vary the cache size in the network, noting that by changing the maximum cache size of CDN servers, the maximum cache size of the ICN routers is correspondingly changed. Other parameters are set to their default values. The results are illustrated in Figure 7,b with the direct comparison of total bandwidth consumption and average content delivery delay under different cache sizes between IECDN and conventional CDN.  
Overall, it is obvious that compared with conventional CDN, IECDN achieves considerable performance gains while reducing bandwidth consumption. Therefore, it is verified that it is favorable to integrate ICN into the CDN architecture. Specifically, with a default cache size of 100 objects on CDN servers and correspondingly 10 objects on ICN routers, the average delay is reduced by approximately 46%, and bandwidth consumption is decreased by around 19%. Meanwhile, it is noteworthy that in the context of CDN, the reduction of bandwidth consumption and average delay exhibits a significant decline when the cache size per server increases from 10 to 200 objects, whereas there are only marginal benefits observed in the wide range of 200 to 500 cache size per server. This phenomenon can be attributed to the inherent characteristics of the Zipf distribution, wherein numerous objects are rarely accessed. The analysis of the impact of Zipf distribution on our proposed design is presented in the following section. A similar but more moderate trend can be also observed in the case of IECDN: when enlarging the cache size, despite a noticeable decline at the beginning, a saturation of both bandwidth consumption and average delay ensues  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **Value** & **Default** \\ \hline Topology & Abilene, Geant2 & Abilene \\ Catalog size & \(1\times 10^{4}\) & - \\ Request number & \(2\times 10^{4}\) & - \\ \(\alpha\) of Zipf & [0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2] & 0.8 \\ Content demand frequency & [10, 12, 14, 16, 18, 20] & 10 \\ Content demand rate [Gbps] & 0.5, 1.0 & 1.0 \\ CDN node cache size [Objects] & [10, 50, 100, 200, 500] & 100 \\ ICN node cache size [Objects] & [1, 5, 10, 20, 50] & 10 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Parameters for numerical analysis.  
Figure 7: Comparison of total bandwidth consumption (**a**) and average delay (**b**) under different cache sizes between IECDN and conventional CDN.  
with minor benefits continuing to be achieved. This enlightened us that less storage cost is required for CDN providers to achieve an adequate performance goal in the presence of in-network caching.
# Insight from Review Articles of Life Cycle Assessment for Buildings
###### Abstract  
The building sector holds a significant position in the global energy consumption share, and its environmental impact continues to intensify, making the construction industry a key player in sustainable development. The application of life cycle assessment on buildings (LCA-B) is widely employed to evaluate building energy and environment performance, and thus is of great significance for ensuring the sustainability of the project. This work aims to provide a systematic overview of LCA-B development based on reviewed literature. A three-stage mixed research method is adopted in this study: Firstly, an overall analysis framework is constructed, and 327 papers related to building life cycle assessment published between 2009 and 2025 are screened out by using the bibliometric method; Then, through scientometrics analysis, the journal regions, sources, scholars, and keyword evolution are revealed and analyzed using VOSviewer tool, and the hotspots in the field of LCA-B (e.g., integration of building information modeling (BIM) in LCA-B, multi-dimensional framework of environment-society-culture) are preliminarily explored based on the selected highly cited papers. The research finds that: (1) the performance of low energy buildings is better than that of net zero energy buildings from the perspective of LCA; (2) software compatibility and data exchange are the main obstacles in the integration of BIM-LCA; (3) a multi-dimensional LCA framework covering the social or cultural aspects is expected for a comprehensive assessment of building performance. This study provides a systematic analysis and elaboration of review articles related to LCA-B and thereby provides researchers with in-depth insight into this field.  
life cycle assessment; bibliometric analysis; sustainability; literature review; VOSviewer tool; building information modeling 2020 IEEE/RSJ Web Conference Conference (2020); 157751
# A Novel Energy-Efficient Contention-Based MAC Protocol Used for OA-UWSN
## 4 OA-UWSN MAC Protocol Simulation Environment Settings  
### Optical Properties of Underwater Channels  
Water is a complex physical, chemical, and biological system. The optical properties of water are related to the three main factors: Pure water, dissolved substances, and suspension [23]. The effects of various components on the beam in a water medium lie in their absorption and scattering effects on the beam [24].
# Comparison of Traffic Flow Models with Real Traffic Data Based on a Quantitative Assessment
###### Abstract
Later literature studies also suggest that the problem is still open [3; 4]. Similarly, it is not clear from the literature, which of the existing models can be perceived as the best and what the criteria would be. The latter are not commonly agreed, and even if used, the assessment or benchmarking of the models is often a subjective matter. The problem of selecting traffic flow model has practical implications. The models representing the relationship between speed, flow, and density serve as a basis for traffic conditions forecasts and assessments such as in the case of United States' HCM [5] or Germany's HBS [6]. Thus, it was also one of the problems to be solved in the context of the recent development of a new Polish method for highway capacity analyses. How to choose the right model for this purpose? What expectations should be given? How to assess whether the model performs well or not? These questions motivated us to the work presented in the paper. The main objective of the article is to review and compare existing models of the fundamental relationship using empirical data from Polish roads. In particular, the article aims to: (1) Identify the criteria to be met by a good model of the fundamental relationship; (2) Develop a transparent and quantitative method for assessing fundamental relationship models based on identified criteria; (3) Assess, compare, and rank the existing models of the fundamental relationship. The paper is organized as follows: Section 2 gives an overview of deterministic mathematical models of the fundamental relationship and criteria and methods for assessing them. Section 3 discusses the proposed methodology for assessing models of the fundamental relationship. Section 4 presents an application of the methodology for field data. The results are discussed in Section 5.
The European Commission Regulation 231/2012 stipulates that the maximum level of 4(5)MEI in ammonia caramel and ammonia sulfate caramel should not exceed 200 and 250 mg/kg, respectively [12]. The International Agency for Research on Cancer has classified 4(5)MEI as Group 2B, indicating that it is potentially carcinogenic to humans [6]. Both the National Toxicology Program and the Office of Environmental Health Hazard Assessment recognize the carcinogenicity of 4(5)MEI [13; 14; 15]. According to the California Environmental Protection Agency, the maximum daily exposure to 4(5)MEI that does not pose a significant level of risk is 29 \(\upmu\)g [16]. These data set the limit of quantification (LOQ) at low levels. Therefore, effective methods are required to accurately monitor 4(5)MEI in food matrices in order to effectively estimate its exposure levels.  
A wide range of analytical techniques have been developed for the analysis of 4(5)MEI in foods and beverages. Liquid chromatography (LC) is the main technique used to determine 4(5)MEI [17; 18; 19; 20; 21; 22; 23], which is mainly hyphenated with mass spectrometry (MS) in order to obtain lower LOQs [24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41]. In addition, analytical methods based on gas chromatography-mass spectrometry (GC-MS) have been applied, although a derivatization step with isobutyl chloroform is required [19; 40; 42; 43; 44; 45; 46; 47; 48; 49; 50; 51; 52]. Moreover, 4(5)MEI has been quantified through UV spectrophotometry [53], capillary electrophoresis [54], paper spray mass spectrometry [55], micellar electrokinetic chromatography [56], high-performance cation exchange chromatography [57], fluorescence-based immunomodographic assay [58], and a fluorescent probe [59].  
The aim of this review is to provide an overview of the methods that have been employed in the last 15 years for the extraction of 4(5)MEI from food matrices, as well as to present the analytical methods and techniques that have been developed for this purpose. The literature research was performed from March to October 2021, using databases, such as Scopus, Web of Science, and PubMed.
## 3 Results and Discussion
### Stability of Mono-Substituted Flavones (n-Hydroxylavones)
This increased planarity facilitates better conjugation between the B-ring and the benzopyrone system, thereby enhancing electronic delocalization. While 4\({}^{\prime}\)-HF also exhibits a small dihedral angle, its hydroxyl group at the C4\({}^{\prime}\) position of the phenyl B-ring is more isolated and interacts minimally with other parts of the molecule. In contrast, the hydroxyl group in 3-HF, strategically positioned at the C3 site of the \(\gamma\)-pyrone C-ring, engages in critical intramolecular hydrogen-bonding interactions. This unique placement allows 3-HF to achieve a balance between electronic delocalization and structural stabilization, distinguishing it from other mono-hydroxyflavones. Despite its extensive hydrogen-bonding network, the stability of 3-HF is determined by a delicate balance between geometric strain, electronic delocalization, and solvation effects. The strain imposed by maintaining a near-planar configuration, combined with the localization of electron density in specific regions, appears to counteract the stabilizing influence of the hydrogen bonds. This interplay explains why 3-HF, despite possessing the most intramolecular hydrogen bonding, ranks as the second least stable among mono-hydroxyflavones.
###### Abstract  
Load frequency control (LFC) is considered to be the most important strategy in interconnected multi-area power systems for satisfactory operation and distribution. In order to transfer reliable power with acceptable quality, an LFC mechanism requires highly efficacy and intelligent techniques. In this paper, a novel hybrid fractional order fuzzy pre-compensated intelligent proportional-integral-derivative (PID) (FOFP-iPID) controller is proposed for the LFC of a realistic interconnected two-area power system. The proposed FOFP-iPID controller is incorporated into the power system as a secondary controller. In doing so, the parameters of the suggested FOFP-iPID controller are optimized using a more recent evolutionary computational technique called the Ant lion optimizer (ALO) algorithm utilizing an Integral of Time multiplied Absolute Error (ITAE) index. Simulation results demonstrated that the proposed FOFP-iPID controller achieves better dynamics performance under a wide variation of load perturbations. The supremacy of the proposed FOFP-iPID controller is demonstrated by comparing the results with some existing controllers, such as fractional order PID (FOPID) and fractional order intelligent PID (FOiPID) controllers for the identical system. Finally, the sensitivity analysis of the plant is examined and the simulation results showed that the suggested FOFP-iPID controller is robust and performs satisfactorily despite the presence of uncertainties.  
interconnected multi-area power system; fractional order fuzzy pre-compensated intelligent PID (FOFP-iPID) controller; ALO algorithm