esa-sceva/satcom-chunk-collection huggingface dataset:
# A Deep-Learning Approach for Diagnosis of Metastatic Breast Cancer in Bones from Whole-Body Scans
## 2 Materials and Methods  
### Breast Cancer Patient Images  
This study was approved by the Director of the Diagnostic Medical Center \"Diagnostico Iatriki A.E.\" and the requirement to obtain informed consent was also waived by the Director of the Diagnostic Center, due to the study's retrospective nature. All procedures in this work were in accordance with the Declaration of Helsinki. A retrospective review of 422 consecutive, previously selected whole-body scintigraphy images from 382 different patients (women) who visited the Nuclear Medicine Department of Diagnostic Medical Center \"Diagnostico Iatriki A.E.\" in Larissa, Greece, between June 2013 and December 2017, was performed. The selection criterion were breast cancer patients who had undergone whole-body scintigraphy, because of suspected bone metastatic disease.  
Due to the fact that there are various remains and non-osseous uptake presented in images (i.e., urine contamination and medical accessories), as well as the frequent visible site of radiopharmaceutical injection [77], a preprocessing approach was accomplished to remove these artifacts from the original images. This preprocessing method was accomplished by a nuclear medicine physician, before the use of the dataset in the proposed classification approach.  
Next, the selected images were diagnosed accordingly by a Nuclear Medicine Specialist with 15 years' experience in bone scan interpretation. In total, 408 bone scan images were selected by the nuclear medicine specialist and classified accordingly into two categories (1) malignant and (2) benign; 221 bone scans concern malignant images whereas 187 bone scans concern benign images without bone metastasis (see Figure 1).  
Figure 1: _Cont._The equipment used for scanning patients is a Siemens gamma camera Symbia S series SPECT System (by dedicated workstation and software Syngo VE32B) with two heads with low-energy high-resolution (LEHR) collimators, where the speed of scanning is 12 cm/min with no pixel zooming. Regarding the procedure followed for bone scintigraphy, two types of radionuclide were used, the 99m-Tc-HDP (TechneScan(r)) and the 99-Tc-MDP (PoltechMDP 5 mg). Approximately 3 h after an intravenous injection of radiopharmaceutical agent, a whole-body scintigraphy was acquired. The dosage of radiopharmaceutical agent ranged between 600 and 740 MBq depending on the body type of the patient, whereas the common intravenous injection is 670 MBq.  
After bone scintigraphy, 586 planar bone scan images from patients with known P-Ca were reviewed, retrospectively. Anterior as well as posterior views of \(1024\times 256\)-pixel resolution were digitally recorded using the whole-body field. The number of detected gamma decays in each spatial unit is represented by images of a 16-bit grayscale depth.
# End-to-End Delay Model for Train Messaging over Public Land Mobile Networks
## 1 Introduction
Furthermore, our model can also be used to study and infer the performance of IoT applications exchanging messages with the ground segment. Finally, the validity of the proposed model has been assessed by comparing the cumulative distribution function of the E2E delays generated by the model with those obtained from measurements. The E2E delay model presented in this paper is obtained from experimental results concerning the terrestrial radio networks only. The paper is organized as follows. In Section 2, we summarize the main characteristics of the experimental setup used to measure E2E delay profile on the selected local/regional railway line. In Section 3, we outline the main features concerning the behavior of E2E delay and the message loss over the railway as emerging from the analysis of the available experimental data. These features are then used to derive the E2E delay model, which is presented in Section 4. The practical usage of the two states E2E delay model is discussed in Section 5. The experimental statistics of the random variables driving the proposed two states model are introduced in Section 6. To prove the ability of the proposed model in reproducing the behavior of the E2E delay, we apply it to an example of a realistic railway scenario. In the same section, we provide results concerning the validation of the proposed model. Finally, conclusions are drawn.
# A Survey on Wireless Body Area Networks for eHealthcare Systems in Residential Environments
## 1 Introduction
### Taxonomy and Requirements
#### 1.2.2 Transmission Reliability and Latency  
Data transmission reliability and latency are two extremely important factors in patient monitoring applications. High reliability and low latency of data transfer ensures that real time data is successfully transmitted and is immediately accessible to healthcare providers. Reliability directly influences the quality of patient monitoring. It can be life-saving in many situations and in a worst-case event; it can be disastrous when a life threatening incident has not been observed or detected.  
On-body channel modeling is another key consideration that has significant impact on the robustness of the communication link. On-body radio propagation channels are mainly influenced by the frequent body movements and dynamic characteristic of the communication channel. Although complicated analysis techniques such as Finite-Difference Time-Domain (FDTD) is able to provide an accurate representation of static on-body radio propagation as shown in [49], extending such analysis into dynamic on-body channel modeling cases is typically too costly. As a result of that many studies focus on statistical techniques or uncomplicated analytical approaches [50; 51].  
In addition, data transmission reliability and latency are mostly relied on the design of Physical (PHY) and Medium Access Control (MAC) layers. In order to achieve optimal reliability and network efficiency, appropriate MAC layer protocols are required to be designed to fulfill the particular needs of specific applications [37; 38]. Reliability of WBAN systems can also be determined in terms of their major Quality of Service (QoS) parameters such as transmission loss rate, delay profile and delay jitter.
## 5 Conclusions  
This paper strove to solve three core problems in the fault detection of water pumps in IRASs. (1) When the equipment has a minor fault, it can still operate normally, but the external manifestations of that fault are inconspicuous. The early prediction of the fault is crucial, and timely warnings for equipment maintenance and upkeep should be provided. (2) The vibration signals are complex and nonlinear, being easily influenced by multiple factors, such as background noise, the vibration of other equipment, and water flow. It is thus pivotal to extract information about the fault's characteristic from both the time domain and frequency domain. (3) Whether the water pump has a minor or serious fault, a certain correlation exists in the vibration signals before and after, so it is necessary to handle the long-distance dependency in the sequence.  
After conducting experiments on hyperparameter adjustment, comparison experiments with commonly used models for fault detection, followed by experimental removals of various modules in the model itself, these results were compared and synthesized with multiple indicators, such as accuracy and precision, for model evaluation. The accuracy of the model proposed here is 91.43%, this being significantly better than that of comparable models.  
As such, this paper's CNN-transformer-BiGRU model can effectively solve the above three problems and meet the performance requirements of the fault detection task in aquaculture and agriculture at large.  
In the future, this model will incorporate signal data such as current and sound to improve multi-sensor data fusion, thereby enhancing the model's diagnostic performance under complex working conditions.  
Conceptualization, H.Y. and W.S.; methodology, H.Y. and W.S.; software, W.S.; validation, W.S. and H.Y.; formal analysis, H.Y. and D.S.; investigation, W.S.; resources, C.Z.; data curation, C.L.; writing--original draft preparation, W.S.; writing--review and editing, W.S. and D.S.; visualization, C.L.; supervision, H.Y.; project administration, C.Z.; funding acquisition, H.Y. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Key Research and Development Program of Zhejiang Province (grant numbers 2023C02011), Zhejiang Province \"San Nong Jiu Fang\" Project (2023 SNJF061, 2024 SNJF063).  
Not applicable.  
The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author.
# Joint Interference and Phase Alignment among Data Streams in Multicell MIMO Broadcasting
## 8 Conclusions  
This paper proposes a robust joint interference and phase alignment scheme based on Bayesian estimation and power distribution among user data streams in the actual MIMO broadcasting communication system. The proposed solution is provided to overcome the simultaneous error and time delay CSI. Theoretical analysis and simulations show that the proposed algorithm improves the system capacity of the system, improves the BER performance, and effectively reduces the impact of time delay CSI on system performance, which indicates its robustness and potential as compared with the existing state-of-the-art algorithms. Future work extensions to this work are to consider a massive number of antennas at the base station and tens of antennas at the user equipment and analyze various important metrics such as energy efficiency, computational complexity, and attenuation under different deployment scenarios. Furthermore, the instantaneous and statistical CSI can be incorporated as an extension of such work so that the system performance evaluation is determined in more detail and from other aspects.  
[PERSON] analyzed the research work and performed experimentations, [PERSON] provided extensive technical support throughout the research work, [PERSON] provided extensive support in the theoretical analysis, and [PERSON] provided the results validation and conclusion. He also provided support in research funding. This work has been partially supported by the \"Ministerio de Economia y Competitividad\" in the \"Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia, Subprograma Estatal de Generacion de Conocimiento\" within the project under Grant BIA2017-87573-C2-2-P.  
The authors declare no conflict of interest.
## 3 Results and Discussion
### Pulsed Electric Fields (PEF) Efficiency  
In order to better evaluate the effect of PEF on the extraction of compounds and to compare it with conventional extraction, the Y\({}_{\text{PEF}}\) efficiency coefficient was introduced. This coefficient is defined as the ratio between the values obtained for chlorophylls, carotenoids (Figure 8a), TPC, TEAC, and ORAC (Figure 8b) with PEF-assisted extraction and those same values obtained with conventional extraction.  
Figure 7: Chlorophyll a, chlorophyll b, and carotenoid content (**a**); TPC, TEAC, and ORAC (**b**) after conventional extraction and PEF-assisted extraction with DMSO/H\({}_{2}\)O. Different lower-case letters in the same parameter indicate statistical differences depending on the extraction time or treatment used.  
The value of Y\({}_{\text{PEF}}\) corresponds to \(\frac{\text{Ca}\left(\frac{\text{mg}}{\text{g}}\text{MS}\right)\text{PEF}}{\text{ Ca}\left(\frac{\text{mg}}{\text{g}}\text{MS}\right)\text{conv.}}\) (for chlorophyll a), \(\frac{\text{Cb}\left(\frac{\text{mg}}{\text{g}}\text{MS}\right)\text{PEF}}{ \text{Cb}\left(\frac{\text{mg}}{\text{g}}\text{MS}\right)\text{conv.}}\) (for chlorophyll b), etc.  
It is important to note that the maximum Y\({}_{\text{PEF}}\) values were observed at the optimum extraction times of 5 and 15 min, independently of the solvent mixture, obtaining a greater effect in the extraction of carotenoids and TPC. From 30 min onwards, Y\({}_{\text{PEF}}\) values decreased rapidly, which gives an idea of the effectiveness of the PEF in extracting these compounds, suggesting that in a reduced time the extraction can be increased, and the cost reduced. In this regard, a recovery of 55-60% for chlorophylls, 85-90% for carotenoids, and 60-70% for total phenolic compounds was obtained with respect to the maximum total content extracted.  
The Y\({}_{\text{PEF}}\) values for TEAC were also increased, as these are directly related to the extraction of the antioxidant compounds. However, this effect was not observed for the ORAC method, as no direct relation between higher extraction and ORAC values was obtained.
# SbMBR Tree--A Spatiotemporal Data Indexing and Compression Algorithm for Data Analysis and Mining
## 2 Related Work  
### Data Compression Methods  
Advances in computer technology for mass storage and digital processing have accelerated to the implementation of advanced data compression techniques to improve the efficiency of transmission and storage [13].  
A Huffman code [14] is an algorithm for computing minimum-redundancy prefix-free codes, which has almost legendary status in the computing disciplines. Huffman coding is often used as a step in compression algorithms, such as the JPEG algorithm.  
The JPEG algorithm is a well-known lossy compression algorithm. In 2005, [PERSON] introduce the JPEG algorithm, which is based on the Discrete Cosine Transform (DCT) [15]. In 2008, [PERSON], [PERSON], [PERSON], and [PERSON] used a detection algorithm for zero quantized DCT coefficients in the JPEG algorithm. The experimental results show that the proposed algorithm can significantly reduce the redundant computation and speed up the JPEG algorithm [16]. In 2012, [PERSON], [PERSON], and [PERSON] introduced a performance evaluation method of the JPEG algorithm based on symbol reduction [17].  
LZ77 is a universal algorithm for sequential data compression. It is a kind of lossless algorithm and is proposed by [PERSON] in 1977. In that paper, the compression algorithm is described in detail, and experiment results show that the performance of LZ77 is comparable to certain optimal fixed codebook schemes designed for completely specified sources [18].  
In addition to the algorithms mentioned above, there are also many compression algorithm schemes, such as Deflate [19], GZIP [20], LZO [21], LZ4 [22], and Delta-encoding [23]. Most of them are based on the LZ77 algorithm and Huffman coding. For example, Delta-encoding is a traditional solution to reduce communication or storage costs. It can reduce data size and improve compression proportion by calculating the difference between adjacent samples. Delta-encoding will significantly improve response size and speed for an important subset of HTTP content types [23]. However, the disadvantage of Delta-encoding is that it is very sensitive to noise in the data, which can result in large differences between adjacent samples, leading to unsatisfactory compression results.  
These traditional compression algorithms mentioned above tend to achieve only higher compression ratios, compression efficiency, or better universality, but this is often not conducive to data indexing and querying. These issues motivate the research presented in this paper.
# Study of the Properties of Human Milk Fat Substitutes Using DSC and GC Methods
## 4 Discussion
Oxidative stability does not only depend on the FA composition and free FA content. Stability may also be affected by the content of antioxidants. Vegetable oils like rapeseed oil contain natural antioxidants such as tocopherols, tocotrienols, phenolic compounds, or phytosterols. The inferior stability of mixtures of lard and rapeseed oil after intereesterification, as compared to the starting materials, may be related to the loss of these natural antioxidants during the process [20; 41]. The oxidative stability of fats and oils is also related to the distribution of FAs in the TAG molecules. During intereesterification the distribution of FAs changes and it may affect the oxidative stability [42]. The activation energies for the thermal oxidative decomposition of the fats obtained in this work correlate with the data mentioned in the literature [24]. The results indicate that E\({}_{\text{a}}\) should not be the only parameter of comparison for analyzed fats and oils. Intereesterification land with rapeseed oil is a very complex blend, containing mainly triacylglycerols. These compounds are highly diverse in terms of chain length and degree of unsaturation of FAs and their position. Such variety influences the oxidative stability. During the measurement at the same time there are some reactions that are characterized by a different constant rates and DSC detects only the reactions with the highest exothermic effects. This can be an explanation of why changes in the effective activation energy, according to the compensation theory, have no physical significance [24].
## 3 Experiments
### Experiment Results of HIL Emulation  
The MR2 HIL device [13], as shown in Figure 17 provides a safe environment for motor drive and control verifications, and it contains a real-time virtual interface of reduced-order motor models, dynamometer, various dynamic load models and power stages. As the control board sends Pulse Width Modulation signals (as control signals) to the six virtual driving gates, the device outputs three-phase current, DC BUS, and position sensors information (as feedback signals) for the control board to drive the motor. The physical motor and power stage mentioned in Section 3.1 can be reconstructed in the HIL system and first-hand verify the control methodology. The cogging torque can be created in any waveform based on the electrical angle, which is chosen to be sinusoid in this verification.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Driver Spec.** & **Value** \\ \hline Rated Output Power & 1.5 kW \\ Rated Output Current & 8 A(\(RMS\)) \\ Rated Input Current & 12 A(\(RMS\)) \\ Rated Input Voltage & 200 \(\sim\) 240 V \(\cdot\) 50/60 Hz \\ Carrier Frequency & 5 \(\sim\) 15 kHz \\ \hline \hline \end{tabular}
\end{table}
Table 2: Driver specification.  
Following the experiment design process mentioned in Section 3.2, the most appropriate operation speed is found to be 1 Hz (30 rpm) as depicted in Figure 18a and the SSSE is 47.9255 (rpm). As the online torque compensation is applied, the SSSE drops significantly to 10.7347 (rpm). The offline cogging torque table can be obtained by averaging the observed information for five turns. The comparison between the offline cogging torque table and HIL preset value is shown in Figure 19.  
Turn off the online torque compensation and apply the offline torque compensation strategy; then, gradually decrease the speed command. The steady-state speed responses are shown in Figure 18b. The lowest controllable speed can be found at 0.2 Hz (6 rpm). For the SSSE at 1 Hz, 0.5 Hz, and 0.2 Hz, the corresponding steady-state speeds are 10.8306 (rpm), 12.0822 (rpm), and 9.3978 (rpm)  
Figure 19: Estimated offline cogging torque table compared with the HIL cogging torque model.  
Figure 17: MR2 series Hardware-in-the-Loop (HIL) connects with control board.  
Figure 18: **(a)** Speed comparison before and after online torque compensation; **(b)** Speed response after offline torque compensation.  
respectively. Since the cogging torque model in HIL is perfectly emulated, the SSSE of offline and online compensation are close, and the noise and uncertainty reduction effect cannot be well observed.  
Then, we turn off the torque compensation and find the most appropriate operation speed under the rated load. It can be found to be 1 Hz (30 rpm), and the SSSE is 48.9357 (rpm), as shown in Figure 20a. Apply the offline torque compensation strategy, and gradually decrease the speed command. The steady-state speed responses are shown as Figure 20b. The lowest controllable speed can be found at 0.3 Hz (9 rpm). For the SSSE at 1 Hz, 0.5 Hz, and 0.3 Hz are 11.5851 (rpm), 13.8724 (rpm), and 12.8187 (rpm) respectively.
# End-to-End Service Availability in Heterogeneous Multi-Tier Cloud-Fog-Edge Networks
## 3 Materials and Methods
### Multi-Tier Systems
A link represents communication between two nodes. It can be represented as \(E\left(N_{ij},N_{v\eta}\right)\), where \(N_{ij},N_{v\eta}\) are nodes. Because of our hierarchical model, \(i\) should always be one unit less than \(\
u\) (i.e., \(\
u=i+1\)), denoting the vertical connectivity between adjacent levels. This representation simplifies the hierarchical nature by only capturing the vertical connections between nodes in adjacent levels. The lack of distinction between primary levels and sublevels streamlines the model while retaining the essence of the hierarchical structure and main characteristics of multi-tier systems:  
* These systems can dynamically adapt to different scenarios, allowing for customized deployments based on specific geographic or operational requirements. * Additional tiers can lead to reduced data travel distances and, consequently, lower latency, which is crucial for applications demanding near instantaneous responses. * By adding or removing tiers based on demand, multi-tier systems can be seamlessly scaled up or down, accommodating fluctuating data volumes and processing needs.
# Analysis of Equivalent Flexural Stiffness of Steel-Concrete Composite Beams in Frame Structures
## 3 Parameter Analysis
### Length of the Negative Moment Region  
The length of the negative moment region is an important indicator in the design of composite frame beams. As shown in Figure 6, the length of the negative moment region is closely related to critical parameters \(K\) and \(\alpha\). Generally, the length of the negative moment region increases with the increase in parameter \(K\). When parameter \(K\), indicating the constraint stiffness at the ends of the composite beam, is zero, the frame beam degenerates to a simply supported beam, and thus, there is no negative moment region in the composite beam. As parameter \(K\) increases from 0 to 10, the length of the negative moment region increases rapidly, whereas when \(K\) exceeds 10, it keeps increasing, but at a relatively lower rate.  
As discussed in Section 3.2, parameter \(K\) in the range of 0 to 10 represents composite beams designed with large spans and heavy loading conditions. In this case, the length of the negative moment region is sensitive to the constraint stiffness at the beam ends; thus, parameter \(K\) significantly affects the cracking of the concrete slab and the flexural stiffness distribution of the composite beam. However, in the traditional method for evaluating the effective flexural stiffness of a composite beam, the length of the negative moment region is generally taken as a constant without considering the boundary conditions. For example, GB 50017-2017 [28] and Eurocode 4 [29] define the negative moment regions as the segments with a 15% length of the span at both the beam ends and assign \(EI^{-}\) as the section flexural stiffness of the negative moment segments. The horizontal line representing the ratio of the length of the negative moment region to the beam span at 15% is also plotted in Figure 6. It indicates that a fixed value of 0.15 overestimates the length of the negative moment region, and overstating the cracking effect of the concrete slab results in a relatively smaller calculated value of the flexural stiffness of the composite beam.  
When parameter \(K\) is fixed, the length of the negative moment region decreases with the increase in parameter \(\alpha\), i.e., the ratio of the linear stiffness of the composite beam before and after the concrete slab cracking. This is because, for a composite beam with a large sectional flexural stiffness in the non-cracked area, a large proportion of the internal force is shared by the positive moment region, and consequently, the cracking area, i.e., the length of the negative moment region, decreases.