esa-sceva/satcom-chunk-collection huggingface dataset:
# Fine-Tuning Large Language Models for Kazakh Text Simplification
## 4 Experiments
### Model Setup and Training  
Two variants of the Seq2 Seq models were explored: a small and a large version. Both models share the same overall architecture and training settings, including two-layer LSTM encoder and decoder, a dropout rate of 0.3, a batch size of 128, and the use of the Adam optimizer with a learning rate of 1e-3. Early stopping is applied with a patience of 20 epochs to prevent overfitting. The small model uses an embedding dimension of 128 and a hidden size of 256, while the large model doubles these values with an embedding dimension of 256 and a hidden size of 512.  
For all three LLM models, LoRA was applied to the transformer layers using rank-32 adapters with a dropout of 0.1. Fine-tuning is performed using the constructed training set of parallel complex and simplified Kazakh sentences. LLMs are trained with the AdamW optimizer, a learning rate of 2e-5, a batch size of 8, and for 3 epochs. All preprocessing steps, including tokenization, follow the original tokenizer associated with each model.  
Figure 2 shows the training loss comparison between small and large Seq2 Seq models. The larger model converges significantly faster and achieves a lower final training loss, indicating greater learning capacity and better optimization behavior. In contrast, the small model converges more slowly and stabilizes at a higher loss, which may indicate underfitting due to limited model expressiveness. This comparison confirms that increased model capacity contributes positively to the learnability of the simplification task.  
\begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline
**Dataset** & **avg\_tokens** & **max\_tokens** & **min\_tokens** & **median\_tokens** & **avg\_chars** & **vocab\_size** & **TTR** \\ \hline Train–Complex & 21.32 & 421 & 5 & 19 & 148.94 & 50,667 & 0.2728 \\ Train–Simple & 16.20 & 284 & 1 & 15 & 113.60 & 34,791 & 0.2466 \\ Test–Complex & 22.47 & 446 & 7 & 20 & 158.42 & 6749 & 0.6007 \\ Test–Simple & 16.90 & 238 & 1 & 15.5 & 119.28 & 4770 & 0.5646 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Token and character-level statistics for complex and simple sentences in each dataset split. TTR—type token ratio.  
Figure 3 presents the training loss trajectories of the KazSim model fine-tuned on three large language models: Qwen2-72B, Llama-3.2-3B, and Llama-3.3-70B. Among them, Llama-3.3-70B achieved the lowest and most stable training loss throughout, indicating better alignment with the target simplification objective. The 3B model shows higher and more volatile loss, while Qwen2-72B demonstrates intermediate behavior.
## 2 Methodology
### Corpus Evaluation
#### 2.3.1 Evaluation Criteria  
Following the categories of intonational phonology (that is, intonation, accent and prosodic organization) [36] and the learning objectives included in PRADIA, the following criteria were used to judge the participant's production by both the prosodic expert and the therapist:  
* Intonation: adjustment to the expected modality. That is, if the target sentence must be interrogative and the speaker manages to model the intonation of a question, it is labeled as correct; otherwise, for instance, in the set of exclamatory phrases, if the speaker fails to reproduce an exclamatory intonation (within a range of intonation possibilities), the sentence is labeled as incorrect.
* Accent: preservation of the difference between lexical stress (stressed versus unstressed syllables) and accent (accented versus unaccented syllables). The loss of this difference can occur in three directions: (a) when tonal prominence appears in all the syllables, creating an undesired rhythmic effect; (b) when the speaker does not discriminate between stressed and unstressed syllables, as shown by the absence of variation in any of the acoustic parameters of intensity, duration and pitch; and (c) when there is tonal prominence variability but the syllable stress is inappropriately allocated.
* Phrasing: adjustment to the organization in prosodic groups and distinction between function and content words. The sentence is labeled as incorrect if every word is pronounced as if it were in an isolated context, without distinguishing between unstressed and stressed words. The sentence is also considered incorrect when the pauses are inappropriately allocated within the speech chain.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Speaker** & **Gender** & **CA** & **VA** & **STVM** & **NVCL** & **MPercT** & **MProdT** \\ \hline S01 & f & 195 & 84 & 94 & 17 & 69.8\% & 48.3\% \\ S02 & m & 204 & 99 & 134 & 18 & 76\% & 72.1\% \\ S03 & f & 178 & 96 & 78 & 20 & 74\% & 74.7\% \\ S04 & m & 190 & 60 & below 74 & 10 & 60.4\% & 49.8\% \\ S05 & m & 223 & 69 & below 74 & 13 & 56.3\% & 45.7\% \\ \hline \hline \end{tabular}
\end{table}
Table 2: Description of the C1 subcorpus. For each speaker, this table shows Chronological age (CA), Verbal mental age (VA), Short-term verbal memory (STVM), and Non-verbal cognitive level (NVCL). Ages are expressed in months. In addition, the mean percentage of success in perception (MPercT) and production (MProdT) PEPS-C tasks are included.
# Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review
## 6 Discussion
### Limitations  
Despite its contributions, the study has several limitations. First, the review is based on a finite number of papers, and thus, potentially important methods or studies might not have been included. The selection of papers was based on specific search strings and databases, which might have resulted in some bias in the identified methods.  
Second, the practicality and applicability of the methods have been evaluated mostly based on the availability of the source code and the possibility of their application in the given context, not on actual testing or implementation in a real-world warehouse system.  
Third, the study has focused on methods for predicting object trajectories within warehouse systems. Therefore, the results may not necessarily apply to other domains or applications.  
In light of these limitations, future work could aim to conduct more extensive literature reviews, perform practical tests of the discussed methods in real-world warehouse environments, and expand the scope to other relevant applications or domains.
###### Abstract
If the input data contain errors, the errors affect both the TC estimation and final downscaling results. Satellite-derived products, including precipitation and SM, are obtained through modeling procedures. Thus, any satellite-based products inevitably contain intrinsic errors. When coarse resolution data with significant errors are used as input for spatial downscaling, some regression models with high explanatory power may yield downscaling results with poor quality [26; 27]. In such a case, residual correction may not improve predictive performance. When LR and area-to-point kriging (ATPK) are applied to the TC and RC estimations, respectively, ATPRK enables a coherent prediction [2; 28]. That is, the downscaling results are the same as the original coarse resolution input data when upscaled to the coarse resolution. Spatial downscaling aims to predict attribute values at a fine resolution by preserving the properties of the input coarse resolution data. Thus, the preservation of the coherence property is important. However, the application of nonlinear regression models to TC estimation cannot guarantee perfectly coherent predictions. TCs estimated using nonlinear regression models can be normalized to satisfy the coherence property. After upscaling the fine resolution TC to the coarse resolution, the coarse resolution RC is calculated by subtracting the upscaled TC from the input coarse resolution data [16]. Then, the fine resolution RC is estimated using ATPK. However, when the input coarse resolution data contain errors, the coherent prediction might degrade the downscaling results, achieving poor predictive performance. Thus, the input errors inevitably affect the prediction results of ATPRK-based spatial downscaling. To the best of our knowledge, most previous studies have focused on the selection of advanced regression models. The impact of the errors of input coarse resolution data on predictive performance has not been thoroughly investigated. As the quality of spatial downscaling results is subject to that of the input coarse resolution data, it is necessary to analyze the impact of input errors in conjunction with the comparison of different regression models. Such a sensitivity analysis is the primary objective of this study. More specifically, this study aimed to compare the predictive performance of spatial downscaling of coarse resolution remote sensing data for different regression models and different quantities of input errors. Quantitative comparisons were conducted on two datasets, including synthetic Landsat images with different error levels and monthly Advanced Microwave Scanning Radiometer-2 (AMSR-2) SM products. In particular, the predictive performances were evaluated in the context of the sensitivity of different error quantities by comparing different regression models for TC estimation.
## 5 Results and Discussion
### Trace Elements
The La/Th ratio could be useful in inferring the provenance of sedimentary material, by considering that for the UCC [17] and NASC [18] this ratio is around 2.88 while in the case of the average Mid-Ocean Ridge Basalt (MORB) [51] it is estimated to be between 7.2 and 15.6. In the case of Zarafshon samples, La/Th ratios for sediments and soils were 3.23 \(\pm\) 1 and 3.03 \(\pm\) 0.9, respectively (Figure 7a), both of them closer to the UCC ratio of 2.96 [17] and of 2.53 for NASC [18]. Further analysis of the distribution function of mass fraction of eight REE, i.e., La, Ce, Nd, Sm, Eu, Gd, Tb, Tm and Yb, are shown to be closer to the UCC [16] one. This is the same peculiarity that we have noticed in the case of the La/Yb ratio, as well as in the case of Eu negative anomaly (Figure 7b, Table 3). Figure 6: Discriminating bi-plot Th/Co vs. La/Sc (**a**); and ternary Sc-La-Th diagram (**b**) confirming the felsic origin of investigated sediments and soils. A possible explanation of this small discrepancy could be related to an increased U content of which average mass fraction were between 3.04 \(\pm\) 1.38 mg/kg in sediments and 3.8 \(\pm\) 1.5 mg/kg in soils. These results suggest the prevalence of the felsic material and sustains the hypotheses that sediments are the main material of the Zarafshon soils.
# TrojanDetector: A Multi-Layer Hybrid Approach for Trojan Detection in Android Applications
## 4 Experimental Validation
### Limitations  
TrojanDetector has some limitations: Firstly, it is evaluated on just three publicly available datasets (which we believe are sufficient to draw an initial conclusion). Secondly, it exploited simple classifiers; it would be interesting to check the performance of advanced machine learning classifiers, e.g., CNN, Transformers, etc., on these datasets. Finally, TrojanDetector is analysed in offline settings; it would be interesting to extend TrojanDetector to work in online mode to perform this classification in real-time.
## 3 Pull-Out Test  
In the present study, pull-out tests were conducted to evaluate the bond characteristics between the developed matrix and the textile, which composed the FRCM. The main parameters for pull-out test specimens were the type of textile that was used and the weaving type, as shown in Tables 5 and 6. Test specimens that contained carbon fibers were divided according to the type of coating into carbon-E (epoxy) and carbon-A (acrylate). Textile weaving methods are divided according to the type of textile that is used in glue bonding and thread bonding types. Test specimens were fabricated in accordance with ISO10406-1 methods [36]. Each specimen was composed of an embedded region, textile, and grip region, as shown in Figure 4a The embedded region is the part that is embedded in the matrix. This part was fabricated using a cubic form (50 (Width) \(\times\) 50 (Depth) \(\times\) 20 (Height) mm). The embedded length of the matrix and textile was 20 (Length) mm. The total length of the textile was 200 mm, and the grip region was installed at the edge part of the textile using a steel plate. The grip size of the pull-out specimen was 50 (Height) \(\times\) 25 (Width) mm.  
Figure 3: Evaluation of void distribution: (**a**) mortar; (**b**) matrix.  
Figure 2: Evaluation of the water resistance of the matrix: (**a**) specimens; (**b**) dipping.  
As shown in Figure 4b, tests were performed using a UTM (Universal testing machine) with a capacity of 1000 kN, and an LVDT(Linear variable differential transducer) with a capacity of 200 mm was installed to measure the displacement of each pull-out specimen.  
The pull-out test was carried out when the matrix reached 28 days, the loading speed for which was 0.01/min. In the present study, the pull-out bond strength between the matrix and textile was estimated using Equation (1) below:  
\[\tau_{out}=\frac{P}{2L(w_{f}+t_{f})} \tag{1}\]  
Here, \(\tau_{out}\) is the pull-out bond strength, \(P\) is the peak load, \(L\) is the embedment length of textile,\(w_{f}\) is the width of the textile, and \(t_{f}\) is the thickness of the textile.
## 6 Prototype Trial Production
### Performance Test
#### 6.1.1 Resolution Test  
In order to evaluate the prototype's minimum angular resolution, the following procedure was conducted. Firstly, the piezoelectric actuator was adjusted to a position 10 \(\upmu\)m away from its initial position, which is closest to the actual working state. Manual control was then applied with a step size of 2 nm to investigate the mechanism's minimum resolution of motion. The grating measurement system recorded data at intervals of 100 ms. The resulting data, depicted in Figure 10, reveal a distinct step-like pattern. The minimum angular resolution of the mechanism's rotation was found to be 50 nrad, comparable to the floor noise level of the grating measurement system, which is also approximately 50 nrad.  
Figure 9: Prototype of the optical angle nano-positioning mechanism.
## 3 Results and Discussion
### For Evaluation of Gas Hydrates Kinetics  
#### 3.3.1 Hydrate Formation Rate  
Gas hydrate is formed by the above-mentioned experimental procedure. The multiphase system with crude oil + deionized water + CO\({}_{2}\) gas and gasoline + deionized water + CO\({}_{2}\) gas is used for the formation of gas hydrates. Once the gas hydrates are formed, the system is maintained at 274 K for almost 6 h. This time is considered adequate time provided to the multiphase system to achieve thermal equilibrium. Then, the system is depressurized by releasing the Gas in the reactor cell and allowed to reach atmospheric pressure. Then, the valves are closed again, and the gas hydrate is maintained in the reactor cell at a constant temperature. The pressure of the system was recorded continuously for almost four days. The formation rate was calculated from the slope of the P-t curve that is displayed in Figure 7.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**System**} & **Initial** & **Initial** & **Equilibrium** & **Equilibrium** \\  & **Pressure** & **Temperature** & **Pressure** & **Temperature** \\ \hline \multirow{4}{*}{Deionized water + Carbon dioxide} & 2.5 & 285.15 & 2.476 & 277.21 \\ \cline{2-5}  & 3 & 285.15 & 2.999 & 278.80 \\ \cline{2-5}  & 3.5 & 285.15 & 3.488 & 280.05 \\ \cline{2-5}  & 3.8 & 285.15 & 3.754 & 281.31 \\ \hline \multirow{4}{*}{Gasline + Deionized Water + Carbon dioxide} & 2.5 & 285.15 & 2.561 & 277.26 \\ \cline{2-5}  & 3 & 285.15 & 2.911 & 277.89 \\ \cline{2-5}  & 3.5 & 285.15 & 3.47 & 279.05 \\ \cline{2-5}  & 3.8 & 285.15 & 3.765 & 280.05 \\ \hline \multirow{4}{*}{Crude Oil + Deionized Water + Carbon dioxide} & 3 & 285.15 & 2.983 & 279.45 \\ \cline{2-5}  & 3.5 & 285.15 & 3.431 & 280.75 \\ \cline{1-1} \cline{2-5}  & 3.8 & 285.15 & 3.659 & 281.15 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Thermodynamic Equilibrium Conditions.
# On Reliable and Efficient Data Gathering Based Routing in Underwater Wireless Sensor Networks
## 13 Conclusions  
In this paper, we have presented the RE-AEDG protocol for UWSNs. The RE-AEDG employs the cooperative routing scheme to improve reliability of data. However, the introduced cooperative routing leads to high energy consumption of nodes. In order to solve this problem, mobile sink is used for data gathering. Also, to further reduce the cost being paid, two optimized versions of RE-AEDG are presented catering the issues of high energy consumption and high E2E delay. Simulation results demonstrate that RE-AEDG has improved data reliability as compared to AEDG and U-LVRP. In the terms of energy consumption and message latency, optimized versions of RE-AEDG perform better than the selected existing techniques.  
RE-AEDG induces additional message latencies, comparative to the counterpart schemes. Since relay selection highly affects the network performance, therefore, a more comprehensive relay selection model to overcome this limitation is under consideration. Moreover, the sink mobility and sojourn time for AUV can be optimized further to reduce the E2E delay.  
**Author Contributions:** [PERSON], [PERSON], and [PERSON] proposed main idea. [PERSON] performed simulations. [PERSON], [PERSON], and [PERSON] did mathematical formulations. [PERSON] and [PERSON] decided flow of and refined the manuscript.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Current Status of Optical Systems for Measuring Lycopene Content in Fruits: Review
## 6 Conclusions  
The current review provides a description of the techniques used for quantification of lycopene contents in various fruits: High-performance liquid chromatography (HPLC), colorimetry, NIR spectroscopy, UV-Vis spectroscopy, Raman spectroscopy, multispectral images (MSI), and hyperspectral images (HSI). The HPLC and spectrophotometry methods can provide more efficient results, but their measurement procedures are lengthy and complicated. In contrast, both multispectral, hyperspectral, and colorimeter imaging techniques are fast and non-contact, and suitable for online applications but still face many challenges regarding their accuracy. NIR spectroscopy, UV-Vis spectroscopy, and Raman spectroscopy are moderately reliable with respect to HPLC. Likewise, current techniques have certain limitations that restrict their comprehensive applications in industrial food inspections. A solution that several research teams are implementing to measure lycopene content in the field is the calibration of colorimeters with respect to HPLC. Studies that considered this method of determining lycopene contents demonstrated that the use of the CIELAB model facilitates the calculations and provides high reliability, although the original color model of the sensors is the RGB model. A relevant finding is that the efficiency in the lycopene measurement in tomato turns out to be more efficient than in other fruits. This motivates the discovery of techniques to improve the estimation in various fruits that contain lycopene. In general, the introduction of artificial intelligence algorithms, the internet of things, parallel processing hardware, and the reduction of equipment costs are areas of future study that lead to the early translation of laboratory results to field applications.  
**Author Contributions:** [PERSON]-J.-V.-A., [PERSON]-G.B.-S. and A.-I.-B.-G.; methodology, J.-A.-P.-M. and J.-E.-B.-A.; validation, A.E.-C.; formal analysis, J.-E.B.-A. and J.-P.-O.; investigation, J.-A.-P.-M.; writing--original draft preparation, [PERSON]-G.B.-S. and M.-J.-V.-A.; writing--review and editing, A.-I.-B.-G.; and supervision, A.-I.-B.-G. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by CONACyT and Tecnologico Nacional de Mexico.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 3 Finite Element Simulation  
### Finite Element Model  
A commercial software package called PZFlex was used to create the finite element model, which is shown in Figure 4. PZFlex is the time domain finite element method (FEM). The complex acoustic wave propagation in a three-dimensional model can be simulated by using this method [32]. The upper and bottom surfaces of the model are free, while the remaining four sides are absorbing. The size of the 6061-T6 aluminum plate is 400 mm \(\times\) 400 mm \(\times\) 1.5 mm, and the other material properties are listed in Table 1. The incident point of the ACT is (100, 200), and its incidence angle is set at 12.75\({}^{\circ}\), which is suitable to actuate the A0 mode on aluminum with the frequency-thickness product of 0.3 MHz\(\cdot\)mm. The damage located at the middle of the plate is a circular flat bottom hole with a diameter of 10 mm and a depth of 1 mm. This damage is surrounded by a rectangular scanning area (60 mm \(\times\) 60 mm),  
Figure 3: Flow chart of the local wavenumber approach.  
which is divided into 121 \(\times\) 121 points with a spatial interval of 0.5 mm. The spatial interval should not be more than half of the wavelength according to the sampling theorem. In our test, the phase velocity of the A0 mode is about 1551 m/s, and the central frequency of the received signal is 200 kHz. Therefore, the wavelength of the A0 mode is 7.775 mm (\(\lambda\) = 1511/200 = 7.775 mm). The sampling interval is only 0.5 mm (\(\lambda/15\)). Apparently, the sampling interval satisfies the sampling theorem and can provide a good spatial resolution. The out-of-plane velocities over the scanning area are recorded by the LDV.  
In this paper, a five-cycle sinusoidal tone burst modulated by a Hanning window with a central frequency of 200 kHz is applied as the excitation signal, which is shown in Figure 5. Eleven specimens listed in Table 2 are used to evaluate the performance of the local wavenumber approach from different aspects.  
Case 1 and Case 2 are used to evaluate the performance of the proposed method when the circular flat bottom hole changes in depth.  
Case 1 and Case 3 are used to evaluate the performance of the proposed method when the circular flat bottom hole changes in radius.  
Case 4 to Case 7 are used to study the impacts caused
###### Abstract  
Underground electrical substations play an increasingly significant role in urban economic development for the power supply of subways. However, in recent years, there have been few studies on the seismic performance of underground electrical substations involving the interaction of soil-structure-equipment. To conduct the study, three-dimensional finite element models of an underground substation are established. The implicit dynamic numerical simulation analysis is performed by changing earthquake input motions, soil characteristics, electrical equipment type and structure depths. According to a seismic response analysis, acceleration amplification coefficients, displacements, stresses and internal forces are obtained and analyzed. It is found that (1) as a boundary condition of soil-structure, the coupling boundary is feasible in the seismic response of an underground substation; (2) the seismic response of an underground substation is sensitive to burial depth and elastic modulus; (3) the oblique incidence of input motion has a slight influence on the horizontal seismic response, but has a significant impact on the vertical seismic response; and (4) the bottom of the side wall is the seismic weak part of an underground substation, so it is necessary to increase the stiffness of this area.  
**Keywords:** underground electrical substation; seismic analysis; influence factor; boundary condition +
Footnote †: journal: Applied Sciences