esa-sceva/satcom-chunk-collection huggingface dataset:
# Binary Numeration System with Alternating Signed Digits and Its Graph Theoretical Relationship
## 4 Graphs Related to Fibonacci Numbers and the Related Numerical System
Suppose these two edges are \(uu^{\prime}\) and \(u^{\prime}v^{\prime}\) with labels \(F_{k}\) and \(F_{k+1}\). Then, due to the \(C_{k-2}(u)\) cycle, the edge \(u^{\prime}v^{\prime}\) is not present in \(\mathcal{F}_{0}\). This confirms statement (b). The claim of this lemma and the fact that \(\mathcal{F}_{0}\) is a tree leads to a new numeral system. The logic is the same: we have a tree defined on the set of natural numbers. From a vertex \(n\), there is unique path to \(0\). This path can be converted to a representation of \(n\). The existence and uniqueness follow from graph theory. Theorem 7.1 (Fibonacci-alternating representation): _Every natural number \(n\) can be written uniquely as a sum_  
\[n=F_{\ell}-F_{i_{1}}+F_{i_{2}}-F_{i_{3}}+\cdots+(-1)^{t-1}F_{i_{t-1}},\]  
_with \(i_{0}=\ell\gg i_{1}\gg i_{2}\gg\cdots\gg i_{t-3}\gg i_{t-2}\gg i_{t-1}\geq 2\), where \(i\gg j\) denotes \(i>j+1\) (i.e. \(i\geq j+2\)); furthermore, \(i_{t-1}\) is even. This sum is called the alternating representation of \(n\)._  
The proof of Theorem 7.1 is based on Theorem 7.1. Proof: Any natural number \(n\) can be considered as a vertex in \(\mathcal{F}_{0}\). There is a unique \(n\to 0\) path in \(\mathcal{F}_{0}\). Let \(n=n_{0},n_{1},\ldots,n_{\ell}=0\) be the sequence of its nodes. \(n=(n+n_{1})-(n_{1}+n_{2})+(n_{2}+n_{3})-\ldots+s\cdot(n_{\ell-1}+n_{\ell})\), where \(s\) is a sign depending on the parity of \(\ell\). The values of the expressions in the brackets are Fibonacci numbers. We obtain the existence of the presentation. For the uniqueness, assume that we have two representations of \(n\). Both of them can be interpreted as the \(0\to n\) path in \(\mathcal{F}_{0}\) (see the proof of the binary case). Since \(\mathcal{F}_{0}\) is a tree, we obtain a contradiction that proves the theorem. As previously, we can extend this representation to integers. We give a few examples of this new representation that we denote by \(F\)-\(Alt\) indices:  
\[-11=\bar{1}0010\bar{1}_{F\text{-}Alt},-10=\bar{1}00100_{F\text{-}Alt},-9=\bar{1 }0100\bar{1}_{F\text{-}Alt},-8=\bar{1}0000_{F\text{-}Alt},\]  
\[-7=\bar{1}0001_{F\text{-}Alt},-6=\bar{1}010\bar{1}_{F\text{-}Alt},-5=\bar{1}0 100_{F\text{-}Alt},-4=\bar{1}001_{F\text{-}Alt},-3=\bar{1}00_{F\text{-}Alt},\]\[-2=\bar{10}_{F-Alt},-1=\bar{1}_{F-Alt},0=0_{F-Alt},1=1_{F-Alt},2=10\bar{1}_{F-Alt},3=100 _{F-Alt},\]  
\[=F_{k+2}+(F_{k+1}+F_{k})-F_{k}=F_{k+2}+F_{k+1}=F_{k+3}.\]0  
\[=F_{k+2}+(F_{k+1}+F_{k})-F_{k}=F_{k+2}+F_{k+1}=F_{k+3}.\]1  
The new numeral system is based on a spanning tree of \(\mathcal{G}\). The graph \(\mathcal{G}\) has many cycles. Finding a spanning tree of it is not natural. There are several ways to construct one. It is possible to describe a different spanning tree and introduce a new numeral system with Fibonacci numbers as place-values. Such numeral systems already exist; for example, see [30; 31] for considered numeral systems. The connection between them and graph theory has not been explored so far.
###### Abstract  
The objective of this study was to develop a heating, ventilation, and air conditioning (HVAC) system optimization control strategy involving fan coil unit (FCU) temperature control for energy conservation in chilled water systems to enhance the operating efficiency of HVAC systems. The proposed control strategy involves three techniques, which are described as follows. The first technique is an algorithm for dynamic FCU temperature setting, which enables the FCU temperature to be set in accordance with changes in the outdoor temperature to satisfy the indoor thermal comfort for occupants. The second technique is an approach for determining the indoor cold air demand, which collects the set FCU temperature and converts it to the refrigeration ton required for the chilled water system; this serves as the control target for ensuring optimal HVAC operation. The third technique is a genetic algorithm for calculating the minimum energy consumption for an HVAC system. The genetic algorithm determines the pump operating frequency associated with minimum energy consumption per refrigeration ton to control energy conservation. To demonstrate the effectiveness of the proposed HVAC system optimization control strategy combining FCU temperature control, this study conducted a field experiment. The results revealed that the proposed strategy enabled an HVAC system to achieve 39.71% energy conservation compared with an HVAC system operating at full load.  
HVAC energy conservation; optimal control; genetic algorithm; FCU group control Article
# Performance Comparisons of Broadband Power Line Communication Technologies
## 2 Structures of PLC
### IoT PLC
#### 2.1.4 Modulation, IFFT, CP/CS Insertion, and Windowing  
For modulations, both coherent and noncoherent schemes are used. For the coherent scheme, QPSK or 16-ary quadrature amplitude modulation (16 QAM) is used. 16 QAM has 16 signal space points, thus 4 bits can be conveyed by one 16 QAM symbol. For a noncoherent scheme, \(\pi/4\)-differential phase shift keying (\(\pi/4\)-DQPSK) is used. With the selected modulation technique, the binary values from the diversity mapper are converted to complex symbols.  
OFDM symbols are produced by an inverse fast Fourier transform (IFFT). By modulation, 1280 complex symbols and their complex conjugates are converted to a real-valued OFDM symbol through a 2560-point IFFT. OFDM symbols have a cyclic prefix (CP) and a cyclic suffix (CS) before and after each symbol, respectively. The CP and CS make symbols resistant to intersymbol interference (ISI). For the CP and CS, 944 and 336 samples are used, respectively. Figure 6 shows an OFDM symbol structure.  
At both ends of the symbol, samples are shaped to have a good power spectrum, and the interval is referred to as roll-off interval (RI), as shown in Figure 6. A detailed description of values in Figure 6 is given in [9]. For the pulse shaping, raised-cosine windowing is used. For the RI, 320 samples are used. The RI is overlapped and added to the adjacent RIs. The sampling frequency \(f_{s}\) is 62.5 MHz. There are 3520 samples in an OFDM symbol period \(T_{s}\), which corresponds to 56.32 \(\upmu\)s. Finally, the OFDM symbols go to the analog interface (I/F) block, and the output signal is transmitted to the receiver through the channel.
# Effect of Waste Engine Oil and Waste Cooking Oil on Performance Improvement of Aged Asphalt
## 4 Results and Discussion
### Softening Point  
The effects of WEO and WCO on the softening point of aged asphalts with different aging times are displayed in Figure 7. It could also be observed that the softening point values of the aged asphalt binders were consistent with the previous conclusion in 4.1 as they decreased with increase in WEO or WCO contents.  
Figure 6: Effects of WEO or WCO on penetration of different aged asphalt.  
As shown in Figure 7, different aged asphalts could reach or exceed the softening point of VA with different oil content. The softening point of asphalts aged 5 h, 7 h, and 9 h recovered up to 93.8%, 93.0%, and 101.0%, respectively, with 1% WEO content. 11 h-aged asphalt recovered up to 104.7% with 2% WEO content. 13-h- and 15-h-aged asphalts recovered up to 101.2% and 103.5% with 3% WEO content, respectively. This proved that WEO could recover some of the aged asphalt's properties, but the effect of WEO content on aged asphalt was better for specific aged asphalt. Meanwhile, the WCO also had a similar effect on softening point. With 1% and 2% WCO contents, asphalts aged 5 h, 7 h, 9 h, 11 h, 13 h, and 15 h were able to recover up to 90.7%, 95.1%, 98.1%, 97.5%, 103.1%, and 94.9%, respectively;  
Figure 7: Effects of WEO and WCO on softening point of different aged asphalt.  
though more WEO or WCO could result in better improvement performance, an excessive amount of oil content would affect other properties of aged asphalt. There was a suitable oil content related to the aging degree of asphalt.
## 3 Experiment and Results
### Transfer Learning Experiment
Additionally, in the training of CFGN using Dataset1, the performance improvement from introducing the model-eye pretrained model was smaller than when introducing the model-eye pretrained model in the training of Dataset2, possibly due to the difference in the precision unit within \(\pm\)1 D between the model eyes with 0.5 D precision and Dataset1, affecting the training results. Observing the entire training process, as shown in Figure 17a, when training ResNet-50-6 using Dataset1, both _ACC_1 and _ACC_0.5 reach convergence within 120 epochs with a pretrained model, whereas without pretraining, 240 epochs are required for convergence. In other cases, the pretrained model also accelerates the convergence speed of the model. Pretraining significantly accelerates model convergence by optimizing parameter initialization and facilitating knowledge transfer. The parameters learned from large-scale data are closer to the potential optimal solution of the target task, avoiding the blind search of random initialization. Additionally, low-level general features (such as the contrast feature of the crescent area in eccentric photorefraction images) can be directly reused, allowing downstream tasks to require only fine-tuning of higher-level structures. Moreover, the implicit regularization effect of pretraining reduces the risk of overfitting, while improved gradient stability and data efficiency--especially in low-sample scenarios--further shorten training cycles. This also means reducing the computation time required for training the network in the cloud, thereby accelerating the deployment of region-specific algorithms. Figure 17: (**a**) The training process of ResNet-50-6 on Dataset1. (**b**) The training process of ResNet-50-6 on Dataset2. (**c**) The training process of CFGN on Dataset1. (**d**) The training process of CFGN on Dataset2. In summary, this section validates that both the ImageNet1k pretrained model and the model-eye pretrained model developed in this study can effectively improve the performance of refractive error screening tasks. Among them, the self-built model-eye pretrained model, being more closely aligned with the target task domain, demonstrates stronger transfer learning capabilities in refractive error screening tasks.
## 2 Simulation of InSAR Parameters, Power, Coherence and Phase
### Effect of Bistatic Fields  
According to the discussion in [PERSON]'s model [17], InSAR coherence is influenced by the four paths of the bistatic field. The Fresnel coefficients utilized in calculating bistatic field occurrences are as follows:  
\[\begin{array}{ll}\Gamma_{sq}=\Gamma_{sq}e^{2 ik_{q}d}&,\ \ \ \ \ \ \ \ \ \,\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \  
Moreover, the reflected-reflected field reduces coherence due to the multiplication of the squares of two Fresnel reflection coefficients. This indicates a notable reduction in coherence, as illustrated in Figure 8 for horizontal components and Figure 9 for vertical components. This important issue is also highlighted in [20]. The terms related to ground-volume-ground reflections, which involve two specular reflections, may have been omitted due to their typically small magnitude resulting from attenuation in vegetation.
## 1 Introduction
The identification of the mental foramen on CBCT can aid in diagnosing pathologies or abnormalities related to the mandible and surrounding structures. It can help detect cysts, tumors, fractures, or any other conditions that may affect the mental foramen area. Therefore, the identification of the mental foramen on CBCT images is an invaluable tool in dental and maxillofacial practices. In the literature, several metrical and morphological parameters were analyzed to correctly assess the anatomical characteristics of the MF, including the maximum height [7] and width [9], the distance from the upper and lower mandibular border [1; 6; 10; 11], the shape [1; 7; 12], the opening angle at the external surface of the mandible [1; 7] and the position according to the teeth [7]. Moreover, some anatomical variants such as the possible anterior loop of the mental nerve [7; 10; 12], its distance from the MF [1; 8; 10] and the accessory MF [8; 12] have been analyzed. However, although most of the literature has so far analyzed different metrical parameters separately for epidemiological purposes, very few articles in the literature have evaluated possible correlations among different metrical measurements commonly used in the surgical localization of the MF. The present article aims at assessing seven different parameters that are useful for MF localization and verifying possible correlations among different measurements and parameters: the results will be useful in improving our knowledge about this important anatomical structure.
# AsGCL: Attentive and Simple Graph Contrastive Learning for Recommendation
## 5 Experiments
### Datasets  
Table 1 contains four statistics, where #User indicates the number of users, #Item indicates the number of items, #Interact indicates the number of interactions between users and items, and Sparsity represents the sparsity of the interaction matrix, which is the proportion of zero elements in the matrix.  
The datasets are available at [[https://github.com/CyberAres/Datasets](https://github.com/CyberAres/Datasets)]([https://github.com/CyberAres/Datasets](https://github.com/CyberAres/Datasets)) (accessed on 28 February 2025). We conduct experiments on widely used public datasets as follows:  
* Gowalla [31] is an important resource for studying social networks, user behavior, and location-based services. It encompasses GPS trajectories, social friendship relations, and location activity classifications. This resource is widely utilized in the fields of social computing, geographic information science, and recommendation systems.
* Amazon-Books [32]. It is a large-scale book review dataset provided by Amazon containing information on book reviews from the years 2000 to 2019.
* Yelp2018 [33]. Based on real feedback and interactions on the platform, it includes a large number of reviews and ratings from various business scenarios across multiple cities. It can reflect user consumption habits and market trends.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Dataset** & **\#User** & **\#Item** & **\#Interact** & **Sparsity** \\ \hline M1-1M & 6039 & 3628 & 836,477 & 96.18\% \\ Gowalla & 29,857 & 40,979 & 1,027,464 & 99.93\% \\ Yelp2018 & 31,608 & 38,044 & 1,561,386 & 99.86\% \\ Amazon-Books & 35,737 & 38,522 & 2,060,674 & 99.85\% \\ \hline \hline \end{tabular}
\end{table}
Table 1: Statistics of datasets.  
Movielens-1M [34]. It comprises a substantial amount of user ratings for a wide array of films, playing a crucial role in personalized recommendation systems and social psychology. The statistical information of the dataset is presented in the table below. Each interaction is considered a positive instance, and a negative pairing is extracted for each user.
# Free-Hand Input and Interaction in Virtual Reality Using a Custom Force-Based Digital Thimble
###### Abstract  
This article presents the Digital Thimble, an index-finger-wearable device designed for free-hand interactions in virtual reality (VR) by varying the touch contact force on a surface. It contains an optical mouse sensor for tracking and a pressure sensor for detecting contact force. A [PERSON] law study compared the Digital Thimble with a commercial finger mouse and a VR controller using both on-press and on-release selection methods. The results showed that the finger mouse provided higher throughput (3.11 bps) and faster speed (1258 ms) compared to the VR controller (2.89 bps; 1327 ms) and the Digital Thimble (2.61 bps; 1487 ms). Further evaluation in sorting and teleportation tasks demonstrated that the Digital Thimble delivered better accuracy and precision. Participants favored the Digital Thimble for its comfort and convenience, highlighting its potential as a user-friendly VR input device.  
F +
Footnote †: journal: Applied sciences  
title=false  
this end, the Digital Thimble was designed and evaluated. This is a portable, force-based, index-finger-wearable device that is always reachable and can be used conveniently and comfortably in various settings and scenarios. The device is equipped with a pressure sensor for detecting contact forces and an optical mouse sensor for tracking finger movements. This optical sensor enables the thimble to be used on a wide range of surfaces, including the human body. This work also investigates two selection methods: _on-press_, which activates upon pressing or applying extra force, and _on-release_, which triggers upon releasing touch or extra force, aiming to accommodate different user preferences and interaction styles.
# Research on Optimized Energy Scheduling of Rural Microgrid
## 7 Conclusions  
In this paper, the short-term prediction of rural load is carried out before energy scheduling. Through load classification and prediction of various rural power loads, the reliability of the input parameters of an energy scheduling system is guaranteed, and the accuracy of the scheduling strategy is improved. In addition, in order to explore the impact of energy-storage capacity on the economics of scheduling strategy, this paper solves the energy scheduling decisions under various capacities and calculates the corresponding costs. It can be seen from the simulation results that with the increase of energy-storage capacity, the cost will decrease firstly and then increase. The total electricity cost of the rural microgrid is minimized at the optimal energy-storage capacity. Because the CES system can provide the rural microgrid with adjustable capacity suitable for daily situations, the method proposed in this paper is cost effective.  
In future, more consideration can be given to the interaction between the CES system and power grid. The energy-storage system in a rural microgrid can no longer be limited to simply powering the homeowner. It can also provide a shared platform for users to help them achieve energy interactions. The service mechanism and service pricing mechanism of CES can be further improved.  
Figure 10: Power dispatching results of rural microgrid: (**a**) load and generation power scheduling result in case 1; (**b**) energy-storage scheduling result in case 1; (**c**) load and generation power scheduling result in case 2; (**d**) energy-storage scheduling results in case 2.  
**Author Contributions:** All the authors made contributions to the concept and design of the article. conceptualization, Z.L. and J.Y.; methodology, Z.L.; software, Z.L. and J.X.; validation, W.J., C.W. and P.Z.; writing--original draft preparation, Z.L.; writing--review and editing, Z.L. and J.Y.; visualization, Z.L. and J.X.; supervision, W.J., C.W. and P.Z.; funding acquisition, J.Y.  
**Funding:** This research was funded by National Natural Science Foundation of China, grant number 61202369 and 61572311, Shanghai Technology Innovation Project (17020500900) and \"Shuguang Program\" sponsored by Shanghai Education Development Foundation and Shanghai Municipal Education Commission (17 SG51).  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Networked Unmanned Aerial Vehicles for Surveillance and Monitoring: A Survey
## 3 Traffic Monitoring
### Research Gap and Future Directions  
Although there is a good number of publications discussing the solutions to traffic monitoring by UAVs, there are still some interesting directions to investigate. For the sensing technique, the available methods often work well in good environmental conditions but do not perform well enough in conditions with weak light and on foggy days. Thus, developing sensing techniques to overcome the influence of environmental factors would greatly promote the usage of UAVs in traffic monitoring. For the control and coordination of UAVs, existing publications mainly focus on the 2D scenario, i.e., the UAVs fly on a certain plane. Though this helps simplify the method design, it does not fully exploit the 3D mobility of UAVs. Therefore, developing approaches for 3D movement with the consideration of fundamental sensing techniques is also an interesting research direction.
# Fog-Computing-Based Heartbeat Detection and Arrhythmia Classification Using Machine Learning
## 5 Results and Discussion  
To evaluate the effectiveness of our system in detecting, analyzing, and interpreting ECG traces, we conducted a series of experiments using the MIT-BIH dataset. First, we evaluated the performance of the heartbeat-detection module as a standalone module and subsequently the performance of the entire system, that is, the heartbeat-detection followed by the arrhythmia-classification module. We evaluated the performance by comparing our approach with selected state-of-the-art solutions from the literature.
## 2 Materials and Methods  
### OCO-2 SIF Data and Flux Tower Data  
OCO-2 was launched on July 2014, with the primary task of collecting space-based global measurements of atmospheric CO\({}_{2}\) column mixing ratios [30]. OCO-2 is equipped with three high-resolution spectrometers to measure reflected sunlight in the 0.76 \(\upmu\)m O\({}_{2}\)-A band and 1.61 \(\upmu\)m and 2.06 \(\upmu\)m CO\({}_{2}\) bands. Such a feature ensures the robust and accurate retrieval of SIF [11]. NASA developed the IMAP-DOAS algorithm to retrieve SIF. We have added the full width at half maximum (FWHM) in our paper, as follows: OCO-2 records high-resolution spectra in three bands: the O\({}_{2}\)-A band (757-775 nm, FWHM = 0.042 nm), a weak CO\({}_{2}\) absorption band (1594-1627 nm, FWHM = 0.076 nm), and a strong CO\({}_{2}\) absorption band (2043-2087 nm, FWHM = 0.097 nm) [13]. OCO-2 has three observation modes: nadir, glint, and target. Typical OCO-2 measurements are collected alternately between nadir and glint mode with a repeat frequency of approximately 16 days. The instrument views the ground directly below the spacecraft in the nadir mode, tracks near the location with direct sunlight reflected in the glint mode, and collects a large number of measurements over calibration/validation sites in the target mode [31]. The viewing zenith angle (VZA) varies, depending on the observation mode applied, and has an impact on the SIF value [19]. Therefore, the observation mode could potentially impact the estimation of GPP. In this work, we used OCO-2 SIF data (OCO2_L2_Lite_SIF.8r). We selected all flux towers in North America, which have both SIF757 and SIF771 data (SIF at retrieval bands 757 and 771 nm) and GPP data spanning from September 2014 to 2018. To obtain more SIF data, we enlarged the area to within 25 km around each flux tower. In particular, the selection of EC sites was based on an assumption of threshold (60%) of International Geosphere-Biosphere Program (IGBP) classifications [32]. Hence, we calculated the maximum land cover of each flux tower. We chose an EC flux tower if the plant type observed at the flux site occupied at least 60% of the corresponding MODIS pixel area within 25 km [24]. However, OCO-2 SIF data of some vegetation types are too sparse, so we broadened this range (minimum is 46%), as shown in Table 1. Finally, we chose 23 EC flux towers (Figure 1). The OCO-2 L2 data contains instantaneous SIF data and a daily correction factor. We used the daily correction factor to convert instantaneous SIF to daily SIF and removed daily SIF with values lower than 0. The GPP values were provided by AmeriFlux, which is a network of PI (flux tower principal investigators)-managed sites measuring ecosystem CO\({}_{2}\), water, and energy fluxes in North, Central, and South America. Network data processing involves performing uniform data quality checks and