esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Conclusions  
The paramount importance of pressure pulsations on compressor operation has been recognized, and investigating their influence is a fascinating topic. A hybrid numerical model is thus developed to consider the interaction between the compressor and the pipeline system. Based on the examinations of the pressure pulsation influence for ideal and real gas models, some main conclusions are summarized below:  
1. Pressure pulsations in the pipeline system can lead to clear oscillations of the in-cylinder pressure and temperature as transferred through the opened valves into the cylinder, especially under the resonance state. Pulsations in the suction system can considerably influence the mass flow rate,  
Figure 13: Variation of the (**a**) compressor mass flow rate, (**b**) indicated power and (**c**) specific work versus harmonic response for ideal and real gas models.  
and the so-called supercharging effect can be obtained if the wave action in the suction system is tuned properly. Furthermore, the discharge resonance increases more specific work needed by suction resonance, for example, by 13% and 10.7% for the real gas model in the first order resonance state.
2. For harmonic responses in the suction system, with the first harmonic response, the compressor mass flow rate is reduced but the specific work is considerably increased; as for the second harmonic, the mass flow rate is raised significantly with a so-called supercharging effect but the specific work is increased slightly, e.g., by 10.2% and 1.6%, respectively, for the real gas. Pressure pulsations at harmonics higher than second order do not have much effect on compressor operation.
3. For harmonic responses in the discharge system, the mass flow rate is changed little by pressure pulsations in harmonic response, but the indicated power and specific work are increased significantly. For instance, the specific work is increased by 13% in the first harmonic response for the real gas.
4. In-cylinder temperature for the real gas model is about 5.9 K higher than that for the ideal gas model during the compression and discharge phases because the mass flow rate that enters the cylinder is higher for the real gas model than for the ideal gas model. Indicated power in the real gas model is slightly higher than that in the ideal gas model, whereas the specific work for the real gas model is less than that for the ideal gas model.  
Conceptualization, [PERSON] and W.J. and Z.D.; methodology, [PERSON] and W.J. and Z.D.; validation, [PERSON] and W.J. and L.L.; formal analysis, [PERSON] and W.J. and L.L.; writing--original draft preparation, Z.L.; writing--review and editing, Z.L.  
This work was supported by the plan project of Qingdao applied basic research (17-1-1-93-jch) and a program of the key research and development plan of Shandong Province (2017 GGX40113).  
The authors declare no conflict of interest.
# A Novel Video Transmission Latency Measurement Method for Intelligent Cloud Computing
## 5 Summary  
In this paper, the generation of latency in video transmission is analyzed and three latency measurement methods are proposed: timecode method, remote online measurement method, and lossless remote video online measurement method. Depending on the deployment scenario, different time latency measurement methods are suitable. The measurement accuracy of Method 1 and Method 3 is similar, but Method 1 is only suitable for local measurement, where the source content is modified with a timestamp. This paper proposes a synchronization framework for Method 3 that balances the out-of-band bandwidth, the measurement accuracy, and the deployment ease using video-aware hash tables. Both Methods 2 and 3 can be used to measure the latency of remote video transmission, but Method 3 does not alter the original video content. One unique value of Method 2 is that it captures the latency of the capturing and the rendering devices (e.g., camera, display). Compared with Methods 1 and 2, Method 3 can achieve high-precision lossless remote video online latency measurement. Method 3 is scalable through today's networks, providing continuous monitoring. This will bring the latency QoS to a level that is then acceptable for next generation applications, including VR and real-time AI solutions.  
In the future, Method 3 can be integrated into cameras, and can directly measure the camera latency. If the camera contains an encoding and decoding system, the video transmission latency can be obtained directly. Furthermore, Method 3 can be extended to not only measure the video transmission latency, but also detect the frame loss in the transmission process.  
Conceptualization, Y.W. and X.B.; Data curation, Y.W. and X.B.; Formal analysis, Y.W. and X.B.; Funding acquisition, Y.H.; Methodology, X.B.; Project administration, Y.W.; Resources, Y.W. and X.B.; Supervision, Y.H. and M.C.; Validation Y.H. and M.C. All authors have read and agreed to the published version of the manuscript. The work is supported by the Natural Science Foundation of Fujian Province of China (2021J01868), Innovation and entrepreneurship team project of Fujian provincial department of education, and a national fund cultivation project of Jimei University ZP2020041. The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
## 6 Proposed Scheme
### Pre-Deployment Process  
In this section, the SG devices \(SD_{i}\) and \(UC_{j}\) must register with \(TA\) before its deployment in SG environments. \(TA\) firstly selects unique identities \(ID_{i}\) and \(ID_{j}\) of \(SD_{i}\) and \(UC_{j}\), respectively. Then, \(TA\) stores the credential information \(\{ID_{i}\}\) in the memory of \(SD_{i}\) and stores the credential information \(\{ID_{j}\}\) in the database of \(UC_{j}\) prior to its deployment in the SG environments.
## 3 Simulation Results
### Water-Incident Transmission Pattern  
Figure 11a shows that the energy was concentrated on the specular-refracted quad near \(\theta=70^{\circ}\) for transmitted light. The energy decreased sharply to zero when it was transmitted away from the specular-refracted quad. Figure 11b presents the horizontal polarization. We find that depolarization was not as obvious as reflectance. The polarization degree of transmittance was above 0.995, while the polarization degree of reflectance was about 0.85, because it is difficult to change the polarization of the light refracted by the wave facets [19]. The 45\({}^{\circ}\) polarization, shown in Figure 11c, arose because transmittance was titled by wave facets. As shown in Figure 11d, the circular polarization was almost zero.  
Figure 10: Reflected energy pattern for polarized water-incident lidar at 45\({}^{\circ}\) incident angle from the nadir and 10 m/s wind speed. The viewing direction is looking upward, facing the specular reflection direction within water. (**a**) I of reflectance; (**b**) \(Q/I\), horizontal polarization (\(>\)0) and vertical polarization (\(<\)0); (**c**) \(U/I\), +45\({}^{\circ}\) polarization (\(>\)0) and \(-\)45\({}^{\circ}\) polarization (\(<\)0); (**d**) circular polarization.
Models based on SVM, PCA, and PLS-DA were applied to discriminate between the spectral contributions of soil samples and those of petroleum and derivatives. In future studies, the predictive models that were developed in the lab can effectively be adapted to detect traces of relevant contaminants in the field. The comparative analyses used are of great importance because they enable the determining of the appropriate statistical tools that should be used to improve the detection of insoluble contaminants in soils and enable better decision making and effectively minimize negative environmental impacts. The importance of this study is that it can be considered as an alternative method to determine soil contamination due to oil spills quickly. Many of the contamination problems posed by the presence of hydrocarbons in soils are because their detection is neither in situ nor timely. For example, certain soils contain traces of oil even after cleanup and are not monitored because oil concentration is considered low (~600-20,000 mg-kg-1, 0.06-2%) [51; 52], rendering them as \"decontaminated.\" In accordance with Dutch legislation (VROM, 1987) [53], there are three limit values of total petroleum hydrocarbons mass per mass of soil: reference (S: 10 mg\(\cdot\)kg\({}^{-1}\); 0.001%), intervention (I: 1000 mg\(\cdot\)kg\({}^{-1}\); 0.1%), and alert (T: 505 mg\(\cdot\)kg\({}^{-1}\); 0.05%). The S value indicates the level at which the soil and groundwater are considered \"clean\". The I value indicates the level above which it becomes a risk to human health and the environment.
## 6 Innovative Technologies Used in Combination with UV-C  
The investigation of the combined effects of different methods and UV-C on the textural attributes of fruits and vegetables is recently come to emerge showing a glimpse of light in the improvement of the surface treatment. However, it is very limited and difficult to examine the advantageous facets as compared to the conventional single UV-C irradiation. Few studies have reported on the combined effects on the textural attributes.  
The quality of strawberries subjected to different patterns of cyclic and repetitive low dose resulted in an improvement in some of the quality parameters. In their study, they exposed the sample at 4 k\(\cdot\)m\({}^{-2}\) prior to storage for single time, two step at 2 k\(\cdot\)m\({}^{-2}\) consecutively at harvest and after four days of storage, and multistep 0.8 k\(\cdot\)m\({}^{-2}\) after zero, two, four, six, and eight days of storage, respectively. From their result, a single step UV-C exposure resulted in a tendency of sustaining higher firmness and delayed softening than the control sample. Two- and multi-step treatments resulted in a higher textural property [107]. The quality of sweet cherry was studied by exposing the fruit to a single and combined operation of UV-B (21.6 k\(\cdot\)m\({}^{-2}\)), UV-C (21.6 k\(\cdot\)m\({}^{-2}\)), and combination with a coating of the sample with 1% chitosan for 24 days and 8\({}^{\circ}\)C. Their result indicated that the combination of UV-C, UV-B, and chitosan coating was able to slow the weight loss and maintain firmness better than the control sample in comparison to the singular effects [152]. In a similar study, grapes treated at 6 kJ/m\({}^{2}\) UV-C and 0.5% chitosan reduced weightlessness. A combined treatment of UV-C and Chlorine dioxide (ClO\({}_{2}\)) on spinach leaves and tomato surface resulted in no significant effect on the texture of the sample after seven days of storage [153]. The combined effect of UV-C irradiation at 2 kJ\(\cdot\)m\({}^{-2}\) and modified atmosphere packaging in cold storage was studied on the quality of cherry tomato, resulting in lower weight loss and maintained firmness [154]. Asparagus exposed to a combined treatment technique of UV-C at 1 k\(\cdot\)m\({}^{-2}\) and ozonized water at 3 ppm for 3 s resulted in improved cutting energy compared to the control over a four-day storage period [70]. The quality of date palm was studied by exposing it to alkaline electrolyte water, neutral electrolyzed water, ozonated water, and UV-C [155]. They found that the combination of neutral electrolyzed water and UV-C treated at 6.22 kJ\(\cdot\)m\({}^{-2}\) resulted in a lower weight loss while a triple combination between neutral, alkaline, and UV-C at 6.22 kJ\(\cdot\)m\({}^{-2}\) brought a higher firmness value as compared to the control and other combinations.
## 3 Experiments and Results
### Detection of Pathologies in Concrete
The results of identifying cracks in the concrete were very consistent but, in some cases, were incorrect. These cases can be solved by using the network dedicated to classification. Figure 5A shows a case of concrete staining that was identified as concrete cracking. There are cases where the shape of these stains can make identification difficult. Figure 5B shows cases where exposed steel was mistaken for cracks in the concrete. Although exposed steel may be accompanied by cracks, in this case the most important pathology to identify would be exposed steel. Figure 5C shows a joint being mistaken for a crack. This case is somewhat complex, as there are unwanted cracks in joints, but it could also be a case of a specific joint for expansion, for example. A specialist would need to assess this case. The detection tests with YOLO, version 8, were performed on 103 images to detect cracks in the concrete, as the dataset was revised to detect cracks. The detection generated 140 artifacts, regions with cracks in the concrete. Only eight of the images analyzed showed false positives. Figure 6 shows a successful case with positive detection with a picture of the CODEBRIM dataset [13], test base. Figure 7 shows a case of an image made by the authors of a real situation. Both cases show that the trained neural network can identify the pathology in the concrete for which it was trained. Figure 5: False positive [13]: (**A**) Corrosion Stain, (**B**) Exposed Bar and (**C**) Joint.
_Remote Sens._**2013**, \(5\), 2857-2882; doi:10.3390/rs5062857  
_Remote Sensing_  
**ISSN 2072-4292**  
www.mdpi.com/journal/remotesensing  
_Article_  
Evaluation of CLM4 Solar Radiation Partitioning Scheme Using Remote Sensing and Site Level FPAR Datasets  
**[PERSON] 1, [PERSON] 2,*, [PERSON] 1, [PERSON] 2, [PERSON] 2, [PERSON] 3 and [PERSON] 3**  
1 Department of Geological Sciences, The University of Texas at Austin, 1 University Station C1100, Austin, TX 78712, USA; E-Mails: [EMAIL_ADDRESS] (K.W.); [EMAIL_ADDRESS] (R.D.)  
2 Environmental Sciences Division, Climate Change Science Institute, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37831, USA; E-Mails: [EMAIL_ADDRESS] (X.S.); [EMAIL_ADDRESS] (W.M.P.)  
3 Department of Earth and Environment, Boston University, 675 Commonwealth Avenue, Boston, MA 02215, USA; E-Mails: [EMAIL_ADDRESS] (Z.Z.); [EMAIL_ADDRESS] (R.B.M.)  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel.: +1-865-576-7815; Fax: +1-865-574-9510.  
_Received: 14 March 2013; in revised form: 3 May 2013 / Accepted: 31 May 2013 / Published: 5 June 2013_  
This paper examines a land surface solar radiation partitioning scheme, _i.e._, that of the Community Land Model version 4 (CLM4) with coupled carbon and nitrogen cycles. Taking advantage of a unique 30-year fraction of absorbed photosynthetically active radiation (FPAR) dataset, derived from the Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) data set, multiple other remote sensing datasets, and site level observations, we evaluated the CLM4 FPAR's seasonal cycle, diurnal cycle, long-term trends, and spatial patterns. Our findings show that the model generally agrees with observations in the seasonal cycle, long-term trends, and spatial patterns, but does not reproduce the diurnal cycle. Discrepancies also exist in seasonality magnitudes, peak value months, and spatial heterogeneity. We identify the discrepancy in the diurnal cycle as, due to, the absence of dependence on sun angle in the model. Implementation of sun angle dependence in a one-dimensional (1-D) model is proposed. The need for better relating of vegetation to climate in the model, indicated by long-term trends, is also noted. Evaluation of the CLM4 land surface solar radiation partitioning scheme using remote sensing and site level FPAR datasets provides targets for future development in its representation of this naturally complicated process.  
**Keywords:** land surface; solar radiation partitioning; climate modeling; evaluation
# A Comprehensive Review on Music Transcription
## 3 Transcription Techniques: Insights and Advances
### Vocal Ensemble Transcription  
Note level transcription in vocal ensembles is a challenging task because vocal lines are simultaneously occurring in an audio recording [56; 57; 58]. The comprehensive review of choir acoustics provided in [56] is particularly valuable for future researchers engaged in vocal transcription studies. The research in [57] investigates the intonation accuracy in four-part of singing (SATB) by comparing individual singers and collaborative ensembles, examining how different listening conditions affect pitch accuracy. Similarly, the work in [58] introduces a spectrogram factorization method for the automatic transcription of a exppella performances with multiple singers. It employs a sparse dictionary of spectral templates for vowel vocalizations and includes a post-processing step using overtone-based features to reduce false-positive in pitch detections. The process in vocal ensemble requires identifying and separating the various vocal lines, estimating the pitches and timings of each line's individual notes, and creating a comprehensive representation of the entire vocal ensemble [59; 51]. The early work in [59] investigated the preferences of experienced listeners for pitch and formant frequency dispersion in unison choir sounds using synthesized stimuli. The later work in [51] utilizes convolutional neural networks for extracting F0 values in ensemble singing. The method is trained on a dataset containing vocal quartets with F0 annotations and is evaluated across various scenarios, including recordings with reverb. Transcription in vocal ensemble is essential for analyzing and understanding multi-part vocal arrangements, harmonies, and interactions between different voices. It has applications in music analysis, arrangement, and synthesis, enabling the recreation of complex vocal textures from recorded performances. The vocal ensemble transcription can distinguish between different vocal ranges--soprano, alto, tenor, and bass--which requires special analysis to extract the individual contributions of each voice [60]. This process enables the reconstruction of multi-part vocal arrangements and the interpretation of polyphonic vocal music [61].
# Adaptive Truncation Threshold Determination for Multimode Fiber Single-Pixel Imaging
## 2 Method
### Experimental Design, Implementation, and Evaluation
#### 2.3.4 Comparative Truncation Threshold Determination Methods  
First, we compared the recovery performance with traditional threshold methods. The following two methods with relatively low computational complexity were used: (1) fixed truncation (\(k_{\text{f}}\)) and (2) [PERSON]'s unbiased risk estimation (SURE). Fixed \(k_{\text{f}}\) was selected directly from the SVs using the index of SV that exceeds 1% of the maximum SV. The SURE requires some computations with knowledge of the noise level. In simulations, the known noise level was adopted for SURE calculations, while in practical experiments, the estimated noise level was used (for details about these two methods, please refer to Appendix B). We did not consider the L-curve and GCV methods in this comparison because their performances are close to that of the clairvoyant benchmark, which can be obtained iteratively, rendering their consideration unnecessary.  
Secondly, we further considered two complex L-curve and GCV instances to compare the time-cost performance with respect to single recovery. Both methods achieved recovery performances approaching that of the clairvoyant benchmark and did not need a targeted prior. The procedure for the L-curve method is as follows: The residual (\(|\mathbf{y}-\mathbf{A}\mathbf{x}_{k}|_{2}\)) and solution norm (\(|\mathbf{x}_{k}|_{2}\)) are computed for each truncation (\(k\)), and the turning point on the plot of the residual versus solution norm is chosen. For GCV, the procedure involves calculating the generalized cross-validation score for each truncation (\(k\)) and selecting the \(k\) value that minimizes the GCV score (\(\|\mathbf{y}-\mathbf{A}\mathbf{x}_{k}\|^{2}/(N_{\text{mea}}-k)^{2}\)). All data processing and experiments were conducted on a computer with the following specifications: Intel(R) Core(TM) i7-9750H CPU @ 2.60 GHz, 2.59 GHz, and 32 GB of RAM.
# Design and Applications of GLANCE: GLanceable Alarm Notification for a User Centered Experience
## 3 Results of the 1 st Macro-Phase: The GLANCE Project
### First Iteration: Dealing with Individual Alarms  
The first iteration was aimed at the achievement of the research objective RO1 (_Definition of an abstract model for the notification of single faults in TLC networks_) and of the problem objective PO1 (_Notification of incoming single alarms_).
# High Reliability Evaluation and Lifetime Prediction of 50 GHz Athermal AWG Module
## 5 Lifetime Estimation  
### Accelerated Life Test  
Accelerated life tests were performed along with the reliability tests to predict the service life of the 96-channel (50 GHz-spacing) athermal AWG. The test estimated the life-stress relationship using the Arrhenius equation by elevating temperatures according to the Meeker and Hahn plan (optimized 4:2:1 allocation), which considers stress extrapolation and time extrapolation to increase the accuracy of lifetime prediction [21].
# UWB Positioning Algorithm Based on Fuzzy Inference and Adaptive Anti-NLOS Kalman Filtering
## 5 Experimental Results and Analyses  
### Architecture of the Positioning Experiment System  
The positioning experiment system designed in this paper consisted of a UWB positioning system and a host computer system. The UWB positioning system had four DWM1000 UWB positioning node modules manufactured by Big Bear Electric Technology Co., Ltd. (Guangzhou, China), as well as a moving vehicle. With STM32F103 as the master control, the DWM1000 modules supported serial communication and multi-tag positioning. The moving vehicle, controlled by an STM32 single-chip microcomputer, supported PS2 remote control, PID speed control and tracking. The measuring distance of the system equipment was about 10 m. The working procedure of the positioning experiment system is described below. The tag node initiated ranging communication in each base station, and then, the ranging data and the corresponding CIR signal characteristic data obtained from each base station were sent to the primary base station. Later, the primary base station gathered the data from all base stations and transmitted them to the host computer via the serial port. After that, data analysis and processing were conducted using the host computer system programed by the QT software, and the processed data were substituted into the designed algorithm modules to obtain highly accurate positioning data, which were eventually displayed on the interface in real time.  
In this paper, static and dynamic positioning experiments were carried out in an actual NLOS environment to compare the positioning algorithm for NLOS error mitigation based on fuzzy inference, the adaptive anti-NLOS KF positioning algorithm and the positioning algorithm combining fuzzy inference with adaptive anti-NLOS KF, so as to verify the performance of the UWB positioning algorithm proposed.