esa-sceva/satcom-chunk-collection huggingface dataset:
# A Seamless Image-Stitching Method Based on Human Visual Discrimination and Attention
###### Abstract  
Stitching gaps and misalignments in mosaic images can severely degrade the human visual perception of mosaic effects. Image stitching plays a key role in eliminating these unpleasant defects. In this paper, an image-stitching method for mosaic images with invisible seams is proposed, according to the research on the human visual system (HVS). By quantifying the human visual attention of images and visual discrimination about luminance difference and fine dislocations, each pixel in the stitching region is given a priority value for tracing a stitching line. Coupled with the processing of an optimal stitching line locating method and the multi-band blending algorithm, the pixels of discontinuous items in mosaic images decrease significantly and the stitching line is almost invisible. This study provides a new insight into the image-stitching field, and the experiments show that the results of the proposed method are more consistent with the human visual system in creating high-quality image mosaics.  
image mosaic; seamless image stitching; human visual system; stitching line detection +
Footnote †: journal: Applied Sciences
# A Study on the Analysis of the Effects of Passenger Ship Abandonment Training Using VR
## 4 Results of Video and VR Passenger Ship Abandonment Training
### Borich Needs Assessment and Locus for Focus Model
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \begin{tabular}{c} **[PERSON]’s Needs** \\ **Coefficient for** \\ **Video Group** \\ \end{tabular} & \begin{tabular}{c} **Locus for Focus** \\ **Model** \\ \end{tabular} & \
\begin{tabular}{c} **Borich’s Needs** \\ **Coefficient for** \\ **VR Group** \\ \end{tabular} &
\begin{tabular}{c} **Locus for Focus** \\ **Model** \\ \end{tabular} \\ \hline Q1 & 4.705 & HH & 3.603 & HH \\ Q2 & 4.575 & HH & 2.720 & HL \\ Q3 & 4.290 & HH & 2.625 & HL \\ Q4 & 4.076 & LH & 2.787 & LH \\ Q5 & 3.734 & HH & 3.578 & HH \\ Q6 & 1.500 & HL & 2.720 & HL \\ Q7 & 1.800 & HL & 1.936 & LL \\ Q8 & 1.625 & LL & 1.950 & LL \\ Q9 & 2.808 & LL & 2.580 & LL \\ Q10 & 2.167 & LL & 2.150 & LL \\ Q11 & 4.050 & HH & 3.425 & LH \\ Q12 & 3.983 & LH & 2.150 & LL \\ Q13 & 5.137 & HH & 3.527 & HH \\ Q14 & 3.466 & LH & 2.234 & LL \\ Q15 & 2.787 & LL & 3.398 & HH \\ Q16 & 1.693 & LL & 3.527 & HH \\ Q17 & 2.540 & LL & 2.588 & HL \\ Q18 & 2.889 & LL & 2.250 & LL \\ Q19 & 3.899 & LH & 3.654 & HH \\ Q20 & 4.543 & HH & 3.734 & HH \\ \hline \hline \end{tabular}
\end{table} 
Table 4: [PERSON]’s needs assessment result for Group 1 (video) and Group 2 (VR). Figure 6: Locus for focus model [12]. From the results obtained from the seafners participating in Group 2 (VR), seven items of Q1, Q5, Q13, Q15, Q16, Q19, and Q20 were identified as items of high importance and low performance Figure 7 (down). The items that were found to be common in both Group 1 and Group 2 were Q1 (understanding and implementation the priority actions of duty officer in the event of an emergency on a passenger ship), Q5 (familiarity and implementation of the crew's behavior while guiding passengers to a safe place in case of an emergency), Q13 (understanding and implementation of the correct abandonship preparation on the passenger ships equipped with life-rafts and MES), and Q20 (understanding and implementation of launching procedures of a life-raft). This indicates that the training for these items needed to be emphasized more in both the video-based and VR-based training methods. Apart from these overlapping items, more reinforced training was required for items Q2, Q3, and Q11 in the video-based training, and more reinforced training was required for items Q15, Q16, and Q19 in the VR-based training.
# Trepenoid Biosynthesis Dominates among Secondary Metabolite Clusters in _Mucoromycotina_ Genomes
## 2 Materials and Methods
### SMC-Encoded Protein Clustering and Annotation  
All putative SMC-encoded proteins were clustered with MCL version 14-137 [28] in a process described in [29]. Based on a sampling of Markov Cluster Algorithm (MCL) cluster silhouette width, a threshold E-value of 1 \(\times\) 10\({}^{-10}\) and an inflation parameter of I = 1.55 were chosen for the final clustering. In parallel, all proteins encoded in each MCL cluster were compared against UniProt/SwissProt (release 2020_03) and MIBIG proteins (release 2.0) with DIAMOND v0.9.34.135 [30]. Hits were computed requiring over 50% coverage of both query and hit protein, using the sensitive mode of DIAMOND. Protein domains and conserved sites were annotated with InterPro (InterProScan-5.45.80 with additional models from PANTHER version 14.1; matches against all optional databases, as well as predictions of coiled coils were conducted. MCL clusters containing representative proteins from at least 10 candidate SMCs were further investigated and labelled manually based on protein domain annotation. Additionally, smaller MCL clusters (at least 2 proteins) were annotated if any DIAMOND hits to the MIBIG 'biosynthetic', 'biosynthetic-additional' or 'transporter' gene categories were found. The annotation results can be found in the Supplementary Tables (Supplementary Table S5, manual annotation of candidate families; Supplementary Table S6, tally of all found similarities to domains/proteins).  
All representatives of candidate families representing nonribosomal peptide synthases (NRPS), putative adenylate-forming reductases (called also non-(nonribosomal)peptide synthase-NPS, i.e., NPS_1, NPS_2, LYS2), luciferase (LUC) and PKS/NRPS hybrids (PKS-NRPS) were further annotated in AdenylPred [31]. Notably, this prediction was initially only possible for 380 sequences (out of 562 in total) where the AMP-binding domain matched the underlying HMMer model with sufficient quality. Upon relaxing the HMM-SEARCH bitscore threshold (set at 50 by default) and separating out individual adenylate-forming domains, further predictions were obtained. All individual predictions, regardless of the HMMer score, are listed in the Supplementary Table S3 (description of SMCs) and Supplementary Figure S2. We performed this prediction for all proteins clustered in the following candidate families harbouring InterPro matches to adenylate-forming domains: MCL0001-NPS, MCL0003-LYS2, MCL0006-NRPS, MCL0048-PKS/NRPS and MCL0862-NPS_2. Malpicyclin/malpibaldin candidate SMCs were inspected based on BLASTP matches to the reference sequences (QOW41315.1, malpicyclin synthetase; QOW41314.1, malpibaldin synthetase) [32].
# Pseudo-Phoneme Label Loss for Text-Independent Speaker Verification
## 2 Related Work
### Loss Function
#### 2.1.4 Triplet Loss  
Triplet loss [35] is often used in face recognition tasks. The advantage of triplet loss lies in the distinction of details. That is, when the two inputs are similar, triplet loss can better model the details, which is equivalent to adding a measure of the difference between the two inputs and learning a better representation of the input.  
Some scholars also introduce triplet loss into speaker recognition tasks. Ref. [36] proposed a TristouNet, a neural network structure based on LSTM, designed to project speech sequences into a fixed-dimensional Euclidean space. Triplet loss is used in training, so that embedding sequences can be directly compared using Euclidean distance. Ref. [37] proposed a neural network-based triplet loss speaker discrimination training method. The Euclidean distance similarity measure is used in both network training and SV testing to ensure that the SV system is trained in an end-to-end manner and achieves significant performance improvements.
## 3 The Proposed Model
### Fully Homomorphic Encryption  
An explanation of the homomorphic encryption (HE) method is provided as follows [22]:  
**Definition 1**.: _(HE): a group of methods\(\{\varepsilon_{k}\}_{k\in\mathbb{Z}_{+}}\) is considered homomorphic in terms of the operator \(\circ\) if there occur decrypt techniques \(\{D_{k}\}_{k\in\mathbb{Z}_{+}}\), so that for any 2 ciphertexts \(c_{1},c_{2}\in C\), the subsequent equality was fulfilled as follows:_  
\[D_{k}(\varepsilon_{k}(m_{1},r_{1})\circ\varepsilon_{k}(m_{2},r_{2}))=m_{1} \circ m_{2},\forall m_{1},m_{2}\in M, \tag{1}\]  
_where \(r_{1},r_{2}\in\mathcal{R}\) denotes the equivalent randomness._The HE method is a pair of methods, \(Enc\) and \(Dec\), with the subsequent features:  
* \(Enc\) obtains as input a plaintext \(m\in\mathbb{Z}_{N}\) and outputs a \(c\) ciphertext so that \(c\) refers to the homomorphic image of \(m\), viz., \(Dec(c)=m\);
* \(Dec\) proceeds to input a \(c\) ciphertext and output a plaintext \(m\) so that \(m\) denotes the homomorphic image of \(c\);
* \(Enc\) and \(Dec\) are calculated as effective. There are 2 categories of HE: multiplicatively HE and additively HE. Additively HE comprises a pair of techniques, \(Enc\) and \(Dec\), to ensure that for each \(m_{1},m_{2}\in\mathbb{Z}_{N}\), \(c_{1}=Enc(m_{1}),c_{2}=Enc(m_{2})\), and \(c_{3}=c_{1}+c_{2}\), ensure that \(Dec(c_{3})=m_{1}+m_{2}\). Multirelatively HE involves a pair of methods, \(Enc\) and \(Dec\), to ensure that for every \(m_{1},m_{2}\in\mathbb{Z}_{N}\), \(c_{1}=Enc(m_{1}),c_{2}=Enc(m_{2})\), and \(c_{3}=c_{1}c_{2}\), ensure that \(Dec(c_{3})=m_{1}m_{2}\). Partially HE is different from HE, but homomorphism is only partially assisted, viz., the encrypt method was homomorphic for some operations but not homomorphic for others. Partially HE is different from fully HE, but homomorphism is only restricted and maintained, i.e., the encryption scheme is homomorphic for some operations while not homomorphic for others. FHE is a kind of HE that permits homomorphism on every function; for instance, the encryption method was homomorphic for every operation. Specifically, an FHE method contains a pair of methods, \(Enc\) and \(Dec\), so that for every \(m_{1},m_{2}\in\mathbb{Z}_{N}\), \(c_{1}=Enc(m_{1})\), \(c_{2}=Enc(m_{2})\), and \(c_{3}=c_{1}c_{2}\), ensure that \(Dec(c_{3})=m_{1}m_{2}\).
## 3 Toward the Generation of Isolated Attosecond Hard X-ray Pulse
### Current Scheme  
We consider a simpler enhanced SASE (ESASE) scheme, as shown in Figure 5. An electron bunch from a linear accelerator is sent to a double-period wiggler magnet. The energy modulation in the electron bunch inside the wiggler is produced by co-propagating a few-cycle CEP stabilized laser. Only a small longitudinal section of the electron bunch interacts with the laser. The peak power of the laser is selected in such a way that the amplitude of energy modulation is significantly larger than the magnitude of random noise in electron energy. The electron beam now enters into a chicane, which introduces dispersion: the higher the electron energy is, the shorter it travels. In general, this leads to the density modulation, producing the microbunching of electrons at a laser wavelength spacing and the periodic current peaks. The increase in the peak current results from a corresponding increase in the energy spread of electrons. Finally, the electron bunch enters into a long undulator so that the microbunching is improved and the current spikes strongly radiate at a resonant wavelength via standard SASE process.  
In our study, the laser wavelengths, FWHM pulse duration and electron bunch energy distributions were optimized to control the side current peaks and to obtain a single isolated attosecond pulse.
## 5 Conclusions  
In this paper, we introduce wav2 wav, a wave-to-wave voice conversion approach enabling end-to-end training, which overcomes the limitations of traditional analysis-mapping-reconstruction methods. By incorporating a feature-extracting CNN into the existing vocoder and by modifying it to act as the generator of the CycleGAN-style voice conversion, the proposed method enables direct conversion from waveform to waveform. Since the proposed algorithm does not depend on any language-specific characteristics, it can be used for voice conversion for languages other than English. Moreover, the proposed method demonstrates the ability to learn effectively, even with a small-sized dataset of just 10 min. Both the objective and subjective evaluations confirmed that the proposed approach significantly improved the quality of converted speech and generated speech that closely resembled the target speech. Due to these characteristics, the proposed method can be used in a variety of applications, such as entertainment [1], education [2], and medicine [3] domains.  
In future research, the proposed method may be extended to singing voice conversion. The method proposed in this study extracts global characteristics encompassing the entire voice of each speaker. Although this method is effective for converting general everyday conversational speech, it is expected that performance may deteriorate in cases where the pitch and rhythm change dynamically within a sentence, such as in a singing voice. Therefore, it will be possible to improve the performance of singing voice conversion by developing a new modeling method that takes into account the fact that speech characteristics can change even in a single sentence.  
Conceptualization and writing--review and editing, I.-C.Y. and D.Y.; methodology, D.Y.; experiment, C.J. (while he was a student at Korea University) and H.-P.C.; writing--original draft preparation, C.J. (while he was a student at Korea University); All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Basic Science Research Program through the National Research Foundation (NRF) of Korea funded by the Ministry of Science, ICT and Future Planning (NRF-2017R1E1A1A01078157). Also, it was supported by the NRF under project BK21 FOUR.  
Not applicable.  
The raw data supporting the conclusions of this article will be made available by the authors on request.  
The author [PERSON] was employed by the company Lotte Innovate Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
# Energy Efficient Framework for a AIoT Cardiac Arrhythmia Detection System Wearable during Sport
## 2 Wearable ECG Design and Dynamic Power Management Strategy
### Ultra-Low-Power Wearable ECG Design
#### 2.1.4 BLE Wireless Communication Module  
Bluetooth is a full wireless protocol that allows devices to communicate over radio waves. Other radio frequency (RF) technologies for low-power, short-range wireless communications are ANT, Zigbee, RF4 CE, Nike\({}^{+}\), and Wi-Fi, among others. Although these technologies are also designed for low-power, short-range, and modest data transfer, they have different range, throughput, robustness, and coexistence capabilities [33]. In this study, Bluetooth-5 (BLE-5) is selected. BLE-5 is the low energy version built-in in the small package Nordic nRF52820 MCU. This circuit represents a good fit for the design of a wearable ECG device. nRF52820 supports all Bluetooth 5.2 features in addition to the Direction Finding, high-throughput 2 Mbps, and long-range features. This chip has an extended temperature range of \(-40\) to 105 \({}^{\circ}\)C, 1.7-5.5 V supply voltage range, and a system current consumption of 0.6 \(\mu\)A in sleep mode and 4.8 mA TX at 0 dBm.
## 1 Introduction
The results are evaluated for satellite formations operating in some scenarios of interest: a SSO with altitude of 530 km, a circular LEO with medium inclination, and a circular lunar orbit with altitude of 4300 km and inclination of 40 degrees. These scenarios have been selected as they are of interest for some formation flying missions analyzed in recent years or under development, including ones in which the author was involved. In particular, it shall be noted that, beyond the popular SSO [1], medium-inclination LEO is attracting growing interest in recent years due to the increasing number of launches, led by the development of the Starlink constellation [23], and due to their suitability for Earth observation and remote sensing applications [24, 25, 26]. Finally, medium-inclination lunar orbits have emerged as a viable solution for lunar navigation systems [27, 28, 29].
## 4 Discussion
### EO Data for Local and National SDG 11 Monitoring  
The first indicator of the \"urban\" SDG 11 acknowledges the importance of ensuring \"access for all to adequate, safe and affordable housing and basic services and upgrade slums\" (SDG 11 Target). However, data to support this target is, at the local level, mostly absent [87]. Commonly, SDG 11 statistics are reported as country-level estimates without the inclusion of local spatial data. Local key stakeholders (e.g., city authorities and communities) do not have easy access to ARD or summative data on their communities [11]. There  
Figure 11: Using OSM pathways, DTM and social-demographic data from Census 2010, it was possible to estimate that more than 24,000 people, depending on public health services, live more than a 15 min walk away of a Basic Health Care Unity and more than 35,000 are more than 15 min (within 16,000 are more than 30 min) walk distance to a 24 h Health Care Unity (adapted from [86]).  
are many relevant data available to capture the geography of deprivation and would allow local experts to set thresholds in data models (e.g., such as the proposed data ecosystem by IDEAMAPS). For example, such data could support defining and prioritising slums for upgrading. However, the presently available data on most cities are patchy, inconsistent and simply not accessible for non-EO or geo-spatial experts. A new initiative, where the authors of this paper are actively part of, is the development of an SDG 11 toolkit [88] that guides local users in accessing EO-based data relevant to local and national SDG 11 reporting. An important element of this toolkit is the offering of capacity building in using such data. The inclusion of communities is also very important to account for the data ethics in terms of empowering access to data and derived information. Furthermore, it is essential to provide easy access for local communities to data about their location and to support their interaction with data systems, e.g., to decide which data should be included and which not. As such, it is also important to cover not only information on what is missing in communities but also about their assets.
## 7 Open Research Areas
### Adaptive Channel Hopping (ACH) Algorithms  
In the previous section, it was discussed that one of the solutions to mitigate interference and multipath fading is channel hopping. In adaptive channel hopping, the channel on a link-by-link basis will be changed when interference is detected on the current operating channel. However, nodes need to collaborate to decide which channel to switch to and this can introduce a significant overhead since nodes need to continuously scan all channels for interference levels and also because nodes need to ensure that while communicating nodes choose the same frequency, neighboring node pairs use different channels. To the best of our knowledge, there are currently no algorithms indicating strategiesto be followed for ACH approaches in multi-hop networks. The challenges in defining the appropriate solutions are overhead and simplicity of the algorithm.
## 5 Conclusions  
We have successfully proposed and reported on an efficient optical-wireless architecture applied to the non-standalone 5G new radio framework and compared the system to related works in the literature. Several distinct electrical- and optical-based fronthaul approaches combining free-space optical, wireless links, and RoF techniques were deployed for selection according to network operator requirements. First, a dual 38 GHz wireless and FSO-based fronthaul architecture enabled a backup link for high-reliability services. Next, a fiber-wireless configuration based on an analog RoF link followed by a wireless extension was studied for simultaneous RF signal distribution of both LTE-A and 5G NR signals. Finally, fiber optics and FSO techniques were integrated into a single fronthaul to extend the fronthaul reach where fiber optics cannot be deployed. After photodetection, further access extension was achieved by wireless signal transmission of the two 3 GPP Release 15 spectral bands of 3.5 and 26 GHz. All three investigated approaches demonstrated performance within the 3 GPP EVM\({}_{\text{RMS}}\) requirements prescribed by 5G NR Release 15. In addition, a VLC access network with carrier aggregation was examined to increase user throughput when immunity to EM interference is paramount. The reported solutions may be integrated in a flexible optical-wireless platform for 5G and beyond, allowing their coexistence with 4G over a shared fronthaul infrastructure. Future works should consider implementation of the proposed architecture to either downlink an uplink or to increase the FSO reach up to hundreds of meters in an outdoor scenario.  
Conceptualization, A.C.S.J.; methodology, R.M.B.; validation, D.H.S. and M.A.R.; formal analysis, R.M.B., D.H.S., M.A.R. and A.C.S.J.; investigation, C.H.d.S.L., E.S.L., M.A.d.O., M.S.B.C., L.C.A., L.G.d.S. and L.A.M.P.; resources, A.C.S.J.; writing--original draft preparation, R.M.B., C.H.d.S.L., E.S.L., M.A.d.O., M.S.B.C., L.C.A., L.G.d.S. and L.A.M.P.; writing--review and editing, R.M.B. and M.A.R.; visualization, R.M.B.; supervision, D.H.S., M.A.R. and A.C.S.J.; project administration, A.C.S.J.; funding acquisition, M.A.R. and A.C.S.J. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was partially supported by RNP with resources from MCTIC, Grant No. 01245.010604/2020-14, under the 6G Mobile Communications Systems project of the Radiocommunication Reference Center (Centro de Referencia em Radiocomunicacoes-CRR) of the National Institute of Telecommunications (Instituto Nacional de Telecomunicacoes-Inatel), Brazil. The authors would also like to thank CNPq, CAPES, FINEP, and FAPEMIG for the financial support.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Modulation Recognition System of Electromagnetic Interference Signal Based on SDR
###### Abstract  
Considering the electromagnetic interference signal in non-cooperative communication, an automatic modulation identification and detection system of electromagnetic interference signal based on software defined radio is proposed. Based on GNU Radio 3.10.7.0 and HackRF One B210 mini, the system estimates the frequency and symbol rate of the interference signal and completes clock synchronization and matching filtering under the condition of unknown a priori information. By extracting high-order cumulants as characteristic parameters, combined with the decision tree classifier, the classification and recognition of six modulation types of interference signals and signal phase correction are realized. This method can distinguish the recognition results in combination with the signal constellation, and complete the real-time reception and recognition of interference signals.  
software defined radio; parameter estimation; modulation identification; higher order cumulant; decision tree +
Footnote †: journal:  
0000-0001-4500-3227][PERSON]  
0000-0002-1891-228]School of Electronics and Information Engineering, Liaoning Technical University, Huludao 125105, China; [EMAIL_ADDRESS]