esa-sceva/satcom-chunk-collection huggingface dataset:
# Data-Free Area Detection and Evaluation for Marine Satellite Data Products
## 4 Discussion
### Analyses of the GOCI, MODIS and OLCI Ocean Color Product Differences
#### 4.2.1 Cloud Detection Algorithm Variance Analysis
The mean reflectance values at the spatial location of the green tide algae in all the data are near 0.045, 0.03 and 0.085. They are greater than the cloud mask threshold mentioned above. However, interestingly, the reflectance values of GOCI and MODIS in the clean water adjacent to the green tide algae within the data-free area do not fluctuate much, with both at less than 0.01, which is much smaller than the threshold of the cloud mask. The excellent cloud detection algorithm of OLCI allows the retention of valid ocean color information, even at spatial locations below 0.05 reflectance (Figure 19c). Furthermore, the range of the magnitudes of reflectance of clean water accompanying the green tide algae within the data-free areas of GOCI and MODIS is essentially the same as that of clean water with no missing information. The cloud mask causes similar spatial and temporal distribution characteristics in the data-free areas of GOCI and MODIS when the environmental conditions within the ocean region are essentially the same. Thus, studying the accompanying phenomena of marine objects in the data-free area can provide a scientific basis for improving and  
Figure 19: The reflectance of green tide algae, clean water in the data-free area and clean water in the area with retained information: (**a**) GOCI, (**b**) MODIS and (**c**) OLCI.
## 5 Monitoring Station  
The automatic monitoring system applied in both roadways was the first of its kind in Polish coal mining, serving as a comprehensive stability control system for the roadway. The underlying assumption was that it would be able to automatically monitor rock movements and pressures on the support cyclically by data recording, and facilitating remote data retrieval.  
The equipment for each measuring station consisted of (Figure 10):  
* load cell sensor installed on the roof arch on specially profiled washers;
* MPBX-type extensometer with a length of 6 m and four measuring levels;
* rock bolt stressmeter with a length of 6 m and six measuring levels;
* load cell sensor installed on the wooden crib;
* two biaxial stresses installed in a coal sidewall (only in PW-1).  
What was unusual in the implemented stressmeters was the method of installing the sensors. They were installed in the sidewalls at an angle of 90 degrees to each other and 45 degrees to the roadway axis, allowing for the determination of resultant changes in vertical and horizontal stresses in both directions, thus providing a triaxial stress state. The schematic diagram of a complete monitoring measuring station is presented in Figure 10.  
The monitoring of stress changes around the excavation was conducted using the ACE 1375 biaxial stressmeter. The applied model was equipped with three vibrating wires set inside a cylinder made of durable steel, evenly spaced at intervals of 120 degrees. Changes in stress in the rock mass can cause deformation of the cylinder casing, resulting in a change in the built-in wires frequency, which activates the coil. This vibration frequency is recorded by a data logger, enabling stress calculations. For this purpose, a calibration card provided by the manufacturer is applied. The stressmeter installation in the borehole was carried out using injection techniques.  
Figure 9: Support schemes in PW-1 roadway: (**a**) Test section I, (**b**) Test section II, (**c**) Test section III.
_Appl. Sci._**2015**, \(5\), 187-208; doi:10.3390/appp5030187  
_Applied sciences_  
**ISSN 2076-3417**  
www.mdpi.com/journal/applsci  
_Article_  
Pilot Study for Investigating the Cyclic Behavior of Slit Damper Systems with Recentering Shape Memory Alloy (SMA) Bending Bars Used for Seismic Restrainers  
**[PERSON] 1, [PERSON] 2 and [PERSON] 2,3,* 1**  
1 Department of Civil and Environmental Engineering, South Dakota State University, Brookings, SD 57007, USA; E-Mail: [EMAIL_ADDRESS]  
2 Department of Civil and Environmental Engineering, Incheon National University, 12-1 Songdo-dong, Yeonsu-gu, Incheon 406-772, Korea; E-Mail: [EMAIL_ADDRESS]  
3 Incheon Disaster Prevention Research Center, Incheon National University, 12-1 Songdo-dong, Yeonsu-gu, Incheon 406-772, Korea  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS], Tel.: +82-32-835-8463; Fax: +82-32-835-0775.  
Academic Editor: [PERSON]  
_Received: 29 May 2015 / Accepted: 22 July 2015 / Published: 30 July 2015_  
**Abstract:** Although the steel slit dampers commonly utilized for aseismic design approach can dissipate considerable energy created by the yielding of base materials, large residual deformation may happen in the entire frame structure. After strong external excitation, repair costs will be incurred in restoring a structure to its original condition and to replace broken components. For this reason, alternative recentering devices characterized by smart structures, which mitigate the damage for such steel energy dissipation slit dampers, are developed in this study. These devices, feasibly functioning as seismic restrainers, can be improved by implementing superelastic shape memory alloy (SMA) bending bars in a parallel motion with the steel energy-dissipating damper. The bending bars fabricated with superelastic SMAs provide self-centering forces upon unloading, and accordingly contribute to reducing permanent deformation in the integrated slit damper system. The steel slit dampers combined with the superelastic SMA bending bars are evaluated with respect to inelastic behavior as simulated by refined finite element (FE) analyses. The FE slit damper models subjected to cyclic loads are calibrated to existing test results in an effort to predict behavior accurately. The responses of the proposed slit damper systems are compared to those of the conventionally used slit damper systems. From the analysis results, it is concluded that innovative steel slit dampers combined with superelastic SMA bending bars generate remarkable performance improvements in terms of post-yield strength, energy dissipation, and recentering capability.  
**Keywords**: slit dampers; superelastic shape memory alloys (SMAs); bending bars; permanent deformation; recentering capability
# Fatigue Characteristics Analysis of Carbon Fiber Laminates with Multiple Initial Cracks
## 3 Experimental Tests
### Static Test  
Following the control variable method, a static testing protocol was devised for the edge crack L\({}_{1}\) and internal crack L\({}_{2}\) as well as the internal crack angle \(\theta\) in carbon fiber laminates. A series of five specimen sets, each with distinct parameter combinations, were fabricated. The detailed parameter configurations and corresponding outcomes are presented in Table 2.  
Post-dissection of the highest load endurance of the test pieces under a variety of conditions, as outlined in Figure 8, it is observed that the maximum load of the carbon fiber laminates diminishes with an increase in the angle of the internal crack L\({}_{2}\), initially starting at 14.762 KN and experiencing a 9.31% reduction. The overall trend of decline is moderate, as indicated by the regression line. With respect to the internal crack L\({}_{2}\) length, the load capacity of the laminates dropped significantly from 14.312 KN at 4 mm to 8 mm, marking a 21.24% decrease. This reduction indicates a notable decrease in load-bearing ability as L\({}_{2}\) lengthens, manifesting a swift downward trend. Additionally, the coefficient of variation reveals that the variability in load capacity narrows as both crack size and angle increase, suggesting that the uncertainty in maximum failure force, in the absence of initial crack length, is predominantly affected by the material's inherent  
Figure 6: Schematic diagram and sample of the specimen.  
Figure 7: Tensile test. (**a**) Test equipment. (**b**) Test process. (**c**) Failure fracture.  
properties. The fracture details in Figure 7 illustrate that during the structural failure of the laminate, interlaminar delamination is initially observed, which is followed by progressive material fracturing until complete structural collapse. The fiber pull-out observed in the fracture zone demonstrates that the fibers and the resin matrix within the carbon fiber board significantly contribute to resisting tensile forces.
## 3 Materials and Methods
### Hand-Crafted Feature Extraction
#### 3.6.1 Gabor Filters  
Gabor filters are widely used for texture analysis due to their ability to capture spatial frequency, orientation, and edge information [26]. The response of a Gabor filter is mathematically expressed as:  
\[G(x,y)=\exp\biggl{(}-\frac{x^{\prime 2}+\gamma^{2}y^{\prime 2}}{2\sigma^{2}} \biggr{)}\cos\biggl{(}2\pi\frac{x^{\prime}}{\lambda}+\phi\biggr{)} \tag{1}\]  
where \(x^{\prime}=x\cos\theta+y\sin\theta\), and \(y^{\prime}=-x\sin\theta+y\cos\theta\). Here, \(\lambda\) is the wavelength, \(\theta\) is the orientation, \(\sigma\) is the scale, and \(\gamma\) represents the aspect ratio.  
In this study, Gabor filters were utilized to highlight the texture patterns associated with _Zyginidia pullula_ damage on maize leaves. The characteristic feeding patterns of this pest create distinctive textures on the leaf surface, which are efficiently captured by Gabor filter responses at multiple orientations and scales.
## 3 Method: Automated Target Detection
### Connection to Satellite Altimetry Data  
In order to decide whether a lake is mapped by one of the satellite altimetry missions, their ground tracks have to be analyzed. For this purpose, the individual measurement locations instead of the nominal ground tracks are used. Thus, for each individual altimetry observation, we verify whether it is taken above one of the detected water bodies. With this strategy, missions on non-repeat orbits such as Saral-DP can also be handled.  
A water body is regarded as being monitored by a mission if at least four valid overflights per year (in average) are detected. This ensures the monitoring of the lake's seasonality even for missionson long or non-repeat orbits (Cryosat-2 and Saral-DP). For the short-repeat missions (Envisat, Jason and Sentinel-3A/B), which cover the same location every 10 to 35 days, the temporal resolution will be always better; i.e., at least once per month.
# Deep Neural Network for Predicting Ore Production by Truck-Haulage Systems in Open-Fit Mines
## 4 Results
### Inference Drawn Using Optimum DNN Models  
Using the optimum morning and afternoon DNN models, ore-production estimates were obtained for five days in the second week of February 2019; the results are illustrated in Figure 11. Table 10 lists prediction-error values for ore production by date. In regards to morning ore production, compared to actual values, ore-production predictions were found to be overestimated by 14.96%, 9.11%, 7.41%, and 4.10% on 9, 11, 12, and 14 February, 2019, respectively, whereas predictions underestimated by 21.42% were obtained on 13 February, 2019, respectively. Morning ore-production predictions for the five days demonstrated an average absolute error of 11.40%. In regards to afternoon ore production, compared to actual values, ore-production predictions underestimated by 22.92%, 4.41%, 12.23%, 2.68%, and 2.12% were obtained on 9, 11, 12, 13, and 14 February, 2019, respectively. The average absolute error in afternoon ore production for the five days equaled 8.87%, which is lower than corresponding to morning ore production by 2.53%. A comparison between the sum of predicted morning and afternoon ore-production value and the actual daily ore production demonstrated the two values to be nearly identical, and the resulting MAPE equaled 4.17%.  
The main reason behind the observed difference in the actual ore production and that predicted by DNN models is that haulage operating conditions, such as the number of trucks dispatched, their dumping-zone stay times, and average travel time, vary in real time during the morning and afternoon hours of operation. Ore production can vary significantly if the number of trucks dispatched during operation is reduced, or a truck is assigned to loading points far away from dumping zones. However, in this study, since ore-production predictions were made by exclusively considering operating conditions at operation-start times, inference errors for validation data were observed to exceed prediction errors.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Date**} & \multicolumn{3}{c}{**Percentage Error (\%) for Ore Production**} \\ \cline{2-4}  & **Morning Operation Time** & **Afternoon Operation Time** & **All day** \\  & **(8:30 a.m.-12:00 p.m.)** & **(1:00 p.m.-4:30 p.m.)** & **(8:30 a.m.-4:30 p.m.)** \\ \hline
2019-02-09 & 14.96 & \(-\)22.92 & \(-\)2.82 \\
2019-02-11 & 9.11 & \(-\)4.41 &
## 4 Hardware Evaluation  
In order to evaluate the Marmote SDR hardware, we created a general development framework along with a prototype baseband application. The framework was designed to be used with various radio front-end modules, including the 2.4 GHz _Joshua_ radio front-end, and to provide valuable insight into the resource usage of the infrastructure components, while the prototype application is meant to serve as a proof-of-concept design for the entire Marmote SDR platform. Such a prototype application also allowed for power consumption comparison with an existing integrated radio chip and a desktop SDR.
# Review of Fast Computation Methods for Finite-State Predictive Control of Multi-Phase Drives
## 3 Fast Computation Strategies
### Reduction of the Allowed Control Set  
The candidate control moves considered during the optimization phase form the Allowed Control Set (ACS). In single-vector FSMPC, this set is typically a subset of the complete set of VSI configurations. In multi-vector FSMPC, the ACS represents a subset of all possible sequences. To maintain clarity, the single-vector case will be discussed first. In this approach, the ACS is often composed of two or more basic VV subsets (e.g., LVV, MVV, etc.). A specific example involves the combination of the LVV set and the ZVV set, introduced in [10].  
Using this idea, ref. [23] introduces an advanced FCS-MPC. This method employs Virtual Voltage Vectors that automatically suppress third harmonic currents, simplifying the cost function by omitting harmonic terms. Furthermore, an Adaptive Control Set dynamically adjusts Voltage Vector amplitudes based on rotor speed, significantly enhancing performance at low speeds. To ensure stability, delay compensation predicts the system state for the next control interval. By achieving an optimal balance between precision and computational efficiency, this approach is highly suitable for demanding applications such as electric vehicle propulsion.  
Likewise, an optimized MPC strategy is proposed in [24], focusing on overcoming the operational performance and computational challenges of traditional methods. The approach introduces a set of 24 Virtual Voltage Vectors uniformly distributed to improve control precision by offering a denser selection of candidates. A novel minimum error duty cycle calculation is included to optimize the relationship between the selected Voltage Vectors and reference currents in the \(d\)-\(q\) axes, minimizing tracking errors. To reduce computational effort, a multi-stage evaluation method is developed, simplifying the vector selection process and reducing the number of evaluations from 24 to 8 cycles.  
A preselection based on deviation in stator current and the change in stator current vector is proposed in [25]. The direction and magnitude of per-unit current vector is considered for a region identification procedure, resulting in a large reduction in computing needs. However, just \(d_{3}\)-\(q_{3}\) harmonic currents are considered.
## 2 Results and Discussion
### Exploring the Volatile Compounds Associated with Baking
#### 2.2.3 Pyrazines  
In the present study, twelve pyrazines were identified in _broas_, although only 2-methyl pyrazine (Pz2) had been previously described [27]. Pyrazines are considered impact odorants, with characteristic pleasant nutty and roasted odor notes [7; 11; 20; 59; 68]. They significantly contribute to the flavor of baked products [11], such as bread [5; 7; 31], popcorn, rye crisp bread [68] and maize products [24]. _Broas_ appear to have a lack of pyrazines when compared to similar foods. Recent studies have shown that the amount of pyrazines varies greatly between different cereal bread [31; 56; 69].  
Although the OT values of alkylpyrazines are relatively high (above 1000 ug L\({}^{-1}\)) [20,68], replacing one or more methyl groups with ethyl can give a marked decrease in the OT. Some ethyl-substituted pyrazines have sufficiently low threshold values to be important in the roast aroma of cooked foods [20]. Taking into account the OTs described for pyrazines and their amount in _proas_, 2-methylpyrazine (Pz2), 2,6-dimethylpyrazine (Pz3) and, especially, 2-ethyl-dimethylpyrazine (Pz9), may be relevant for their overall aroma. The former shows nutty, cocoa, and roasted meat aromas [68]; however, it was described as a possible off-volatile popcorn [33]. 2,6-Dimethylpyrazine was also considered an important volatile in maize meal extruded product with whey protein [24]. Lastly, Pz9 was tentatively identified as 2-ethyl-3,6-dimethylpyrazine or 2-ethyl-3,5-dimethyl-pyrazine since they show similar SI and LRI (Table 1). Both compounds are potent odorants and contribute to cocoa, nutty, potato and roasted notes [51]. 2-Ethyl-3,5-dimethylpyrazine is a key odorant of maize tortilla chips, popcorn and rye bread crust [7,43,70], whilst 2-ethyl-3,6-dimethylpyrazine is a key odorant of maize tortilla chips, taco shell [32,43] and popcorn [33].  
Some pyrazines, such as 2-acetyl-3-methylpyrazine (Pz10), 5_H_-5-methyl-6,7-dihydroxy-clopentapyrazine (Pz11) and 2-(2'-furyl)-pyrazine (Pz12), have not been detected in related food products, but may still be relevant to the aroma of _proas_, since Pz10 and Pz11 may give maize-like aromas to foods [51].
## 2 Case Report  
A 90-year-old man was referred to the Maxillofacial Surgery division of the University Hospital of Sassari on the discovery of an ulcerated lesion of the palate, present for approximately two months [Figure 1]. The patient had multiple comorbidities in his medical history: a previous ethmoidectomy for squamous cell carcinoma (22 years earlier), arterial hypertension, a prior cerebral stroke, hypercholesterolemia, and arterial disease of the lower limbs.  
Figure 1: Pre-operative view of the maxillary tumor.  
An incisional biopsy of the lesion confirmed the diagnosis of squamous cell carcinoma. The patient then underwent a contrast-enhanced CT scan, which revealed a large area of osteolysis involving the left maxilla, extending beyond the midline and encompassing the entire pre-maxilla [Figure 2]. Neck scans showed no suspicious lymphadenopathy.  
The patient was then considered a candidate for total maxillectomy. Given his comorbidities, age, and general state of health, the medical team ruled out the possibility of a free flap, opting instead for a local solution: a temporalis muscle flap. The decision to use a temporalis muscle flap over a buccinator myomucosal flap was guided by several factors. First, given the size of the defect, it would have been necessary to harvest and transpose two myomucosal flaps. The donor site morbidity of cheek flaps is acceptable only if the patient is cooperative. Intensive post-operative exercises and scar manipulation are fundamental to preventing scar retraction on the cheek [28]. This patient did not guarantee such cooperation.  
Additionally, the temporalis flap tends to undergo rapid re-epithelialization, forming scar tissue that is very similar to the keratinized gingiva, making it easier to prosthetize. On the contrary, myomucosal flaps retain a certain bulk, and it would still have been necessary to proceed secondarily to the section of the pedicle to allow for the accommodation of the prosthesis. Thus, considering the overall patient scenario and anticipated outcomes, the temporalis muscle flap was deemed the most suitable option.  
To provide support to the soft tissues of the middle-third of the face and to enhance the prospects for implant-prosthetic rehabilitation, it was also decided to position a custom-made maxillary subperiosteal implant.
# Multilabel Text Classification with Label-Dependent Representation
## 2 Related Work
### Text Representation
On the other hand, according to [38], two important decisions must be made when choosing the representation based on the vector space model. (1) What should a term consist of? What should be a root word, a word, a set of words, or their meaning? (2) How should the term's weighting scheme be? Weighting could be achieved via a binary or inverse document frequency (\(tf\)-\(id\)) function developed by [39] using feature selection metrics such as chi-squared (\(\chi^{2}\)), information gain (\(IG\)), reason or profit ratio (\(GR\)), etc. Term weighting methods improve the effectiveness of text classification through an appropriate selection of term weights. Although text classification has been studied for several decades, term weighting methods for text classification are often taken from the field of information retrieval (\(IR\)), including, for example, the Boolean model, \(tf-idf\), and its variants. In general, to weight the terms in the vector space model, the frequency of the terms or the frequency of the documents containing a term can be used. According to [40], many investigators have worked on the technique of extracting text features trying to maintain the syntactic and semantic relationship that is lost when only words are considered. Additionally, although many researchers have tried novel techniques to solve this problem, they still have limitations. A simple but expensive solution to the syntactic problem is to use the \(n\)-gram technique for feature extraction. Term Frequency (TF)--which assigns each word a number according to the number of times that term appears in the whole corpus--is the most fundamental type of weighted word feature extraction. Word frequency is typically used as a logarithmically scaled or as the Boolean weight in techniques that scale TF findings. In all word weighting methods, each document is translated into a vector (with a length equal to that of the document) containing the frequency of the words in that document. Although this approach is intuitive, it is limited by the fact that certain commonly used words in the language can dominate such representations. In contrast, weighted word functions are based on word counts in documents and can be used as a simple word representation scoring scheme. Each technique presents unique limitations. Weighted words calculate document similarity directly from the word count space, increasing the computation time for large vocabularies. While single word counts provide independent evidence of similarity, they do not account for semantic similarities between words. Word embedding methods address this problem, but they are limited by the need for a huge corpus of text data sets for training. As a result, scientists prefer to use pre-trained word embedding vectors. However, this approach cannot work for words that are missing from these text data corpora.