esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Conclusions  
In this work, we presented season median NmF2/hmF2 observed by FY3C/GNOS and COSMIC during 2016.035 and 2017.035 in four seasons and found that the global ionospheric climatological characteristics probed by FY3C/GNOS are highly consistent with that of COSMIC in typical ionospheric features like the EIA, semiannual anomaly, annual anomaly, winter anomaly, WSA, and so on, though minor discrepancies do exist like the magnitude differences of longitude peak structures and WSA, which shows the significance of the IRO products of FY3C/GNOS in ionospheric climatology study. Besides, this work also for the first time verifies the precision of NmF2/hmF2 of FY3C/GNOS by matching with that of the same type space-based occultation project, COSMIC. The results show that the systematic errors, namely, the biases of NmF2/hmF2 between FY3C/GNOS and COSMIC are close to 0, thus negligible, the overall correlation coefficient and std of NmF2 between FY3C/GNOS and COSMIC is 0.95 and 17.48%, respectively, and the overall correlation coefficient and std of hmF2 is 0.91 and 18.01 km, respectively, demonstrating the decent accuracy consistency of IRO product between FY3C/GNOS and COSMIC.  
Due to the limitation of the number of occultation channels, FY3C/GNOS can only observe about 300 (just for GPS) ionospheric occultation events per day. Therefore, FY3D/GNOS launched in 2017 was enhanced in number of occultation channels and antenna coverage, thus increasing the observednumber of daily ionospheric occultation events to about 500 (just for GPS). With the enhancement of the observation capability of GNOS payload and the gradual implementation of the 3+1 constellation network established by FY3 series satellites (E, F, G and R) [4], the FY3 series occultation project will make more contributions to the international ionospheric climatology research.  
Conceptualization, W.B. and G.T.; Data curation, Y.L., X.M., and D.Z.; Funding acquisition, C.L., Y.C., D.W., Y.W., C.Y., and P.H.; Methodology, W.B. and G.T.; Resources, J.X., C.C., Q.D., X.W., G.Y. and M.L.; Software, W.B., G.T. and Z.L.; Supervision, Y.S.; Writing--original draft, G.T.; Writing--review and editing, W.B.  
This research was supported by the National Natural Science Foundation of China (Grant Nos. 41405039, 41775034, 41405040, 41505016, 41505030 and 41606206), the Strategic Priority Research Program of Chinese Academy of Sciences (Grant No. XDA15007501), the Scientific Research Project of the Chinese Academy of Sciences (Grant No. YZ201129), and the Feng Yun 3 (FY-3) Global Navigation Satellite System Occultation Sounder (GNOS) development and manufacture project led by NSSC, CAS.  
We greatly appreciate CDAAC team for providing the COSMIC EDP data and NSMC for providing the FY3C/GNOS EDP data.  
The authors declare no conflict of interest.
# Thermal Conductivity of Nanofluids: A Review on Prediction Models, Controversies and Challenges
## 2 Thermal Conductivity Measurements Overview
### Laser Flash Method  
The bottom of the fluid is heated with a laser and the temperature on the top of the fluid is measured with a thermometer. The temperature increase can then be correlated with the thermal conductivity. The effects of radiation and convection are minimized by the short time (in the order of nanoseconds) needed to heat the sample [5].
## 4 Simulation Results and Discussion
### Discussion  
This proposed approach is demonstrated by two distinct scenarios, office building and residential building, with the desired scheduling results of various energy generators. The total operational costs in Case 1 and Case 2 are 25223.47 RMB and 13645.52 RMB, respectively. In Case 1, the aggregated EVs are scheduled to discharge to satisfy the electricity demand, along with the CHP units and the connected main grid. In Case 2, the aggregated EVs are dispatched to charge during valley periods and discharge during peak periods. With the effective utilization of TOU electricity pricing and the available aggregated EVs, the economic operation can be effectively achieved by the proposed approach. Take Case 1 as an example to calculate the energy conversion efficiencies of the CHP_I and CHP_II unit, which are \(\eta_{\text{CHP\_I}}\)= 89.17% and \(\eta_{\text{CHP\_II}}\)= 61.85%, respectively.  
As can be seen in Figures 9a and 15a, the general tendency of purchasing electricity power from the external main grid changes is in accordance with the variation of electrical load and electricity price. Comparing Figures 14a and 15a,b, the aggregated EVs are charged at night when the electricity is at a low level price and the power demand is low, and, as a result, more electrical power will be purchased from the main grid. The trend toward higher discharging power ratings can be combined with the peak shaving. In addition, the combination of different facilities is likely to further promote the comprehensive benefit of the MES. A comparison between the experimental data in Figures 9, 10, 15 and 16 shows the tendency of evolutionary processes compatibly, according to the variable electricity price and power consumption. These strategies allow a high number of EVs to be charged or discharged in either office or residential building with a lower impact on the connected main grid and an increased flexible consumption.
# Contract-Based Incentive Mechanism for Mobile Crowdsourcing Networks
## 1 Introduction
Practically, some MUs may want to \"gamble\" too much by crowdsourcing sensing, and the crowdsourcing participants' behavioral features will be influenced by their attitudes on risk. Inspired by these existing works, this work investigates the crowdsourcing incentive mechanism in the presence of asymmetric information with risk attitudes. A contract-based incentive model is proposed to obtain the _effort-incentive_ objective. The _bonus ratio_ related to the MUs' performance is introduced to motivate the MUs to work effectively. The optimal contract designs are investigated by jointly examining both the SP's and MUs' risk preferences. A moral hazard model is proposed to incentivize the MUs to participate in crowdsourcing tasks effectively with asymmetric information. The optimization incentive problem is formulated to maximize the SP's expected utility subject to the feasible conditions of the MUs. The impact of the crowdsourcing participants' risk preferences on the incentive mechanism has been studied analytically and experimentally. Simulations have demonstrated the proposed incentive mechanism's performance. The rest of the paper is organized as follows. Section 2 introduces the system model for the crowdsourcing incentive mechanism. The optimal contract design with risk attitudes is proposed and discussed in Sections 3 and 4, respectively. Section 5 demonstrates the performance evaluation results, and Section 6 concludes this work.
## 1 Introduction  
In modern mining and exploration drilling units, one of the most important installation units (and the main energy consumer) is the mud pumping unit (MPU).  
The energy intensity of the drilling process significantly depends on the efficient operation of the transmission (drive) shaft of the pump, which is accompanied by large dynamic loads [1, 2, 3]. The range of changes in the pump cyclic load directly depends on the operating modes of the drill (start up - braking), the sum of the moments of forces that occur during different periods of drilling, and the deviation angle of the cutter at its entry. The energy efficiency of the pump operation largely depends on the dynamic, power, and energy characteristics of the transmission shaft, the kinematics of the gear and the design features of the drive.  
Its technical condition and maximum permissible life indicators ensure the performance of technological operations that determine the efficiency and energy intensity of the well drilling process [3,4].  
Studying the design and technological features of the pumping and the drilling unit, it was found that there are frequent failures along with its high margin of safety that can be associated with a sharp decrease in the supply pressure, _Ps_, and, as a result, in productivity. In some fields, intensive wear (i\(\rightarrow\)max) of the cylinder-piston and plunger parts of the pump occurs during long-term core drilling at a milling cutter entry angle of up to 45\({}^{\circ}\). This process can be explained by a sharp increase in the moments of resistance forces (Ff,...) with an increase in the supply volume of a special clay-containing solution to the casing head when the milling cutter slows down the speed.  
Since the main criterion for the performance of shafts and gears is their fatigue strength (endurance), for the manufacture of most shafts thermally improved medium-carbon steels 40, 45, and 50 are used. They are used for the manufacture of shafts of stationary machines and mechanisms. The billet made of such steels is subjected to an improving heat treatment (HRC \(\leq\) 36) before machining. The shafts are turned on a lathe, followed by grinding of the seats and trununions on a grinding machine.  
If the endurance of the thermally improved shafts is unsatisfactory or if they have wear sections, the shafts made of these steels are subjected to surface quenching with high-frequency currents heating and low tempering in these places.  
Thus, there is a need to form and systematize the technical and operational indicators of the drilling rig and establish the dependence of changes in the quality criteria of a hardened coating that characterize the efficiency and service life of its operation.
## 3 Preliminaries
### Linear Homomorphic Encryption (LHE)  
Linear homomorphic encryption (LHE) [28; 29; 30] can support limited additive and multiplicative operations on ciphertexts. It is able to compute a linear combination of multiple ciphertexts, which has practical applications.  
Given \(n\) plaintexts \((m_{1},\ldots,m_{n})\), the corresponding ciphertext is \((c_{1},\ldots,c_{n})\). Given \(n\) constant coefficients \((\gamma_{1},\ldots,\gamma_{n})\), the ciphertext of the linear combination \(\sum_{i=1}^{n}\gamma_{i}\cdot m_{i}\) can be computed by \(\{c_{i}\}_{i=1}^{n}\) and \(\{\gamma_{i}\}_{i=1}^{n}\). Next, we describe the LHE algorithms based on the private key version by [PERSON] and [PERSON] [3]. It contains five algorithms: \(LHE=(Setup,KeyGen,Enc,Dec,Eval)\). The details are as follows:  
* \(Setup(\lambda)\to pp\): The security parameter \(\lambda\) is taken as input. Two \(\lambda\)-bit large prime numbers \(q\) and \(p\in\mathbb{Z}_{q}^{*}\) are chosen. Set \(n=2^{\lfloor\log\lambda\rfloor-1}\), and there is a cyclotomic polynomial \(f(x)=x^{n}+1\). \(\chi\) is the discrete Gaussian distribution over the ring \(R_{q}=\mathbb{Z}_{q}[x]/\left\langle f(x)\right\rangle\). The public parameters \(pp\)=\(\{n,f,q,\chi\}\) are obtained as outputs.
* \(KeyGen(pp)\to sk\): The public parameter \(pp\) is taken as input. A ring element \(s\xleftarrow{\xi}\chi\) is a sample, and the secret key \(sk=s\) is obtained as an output.
* \(Enc(sk,m)\to c\): For a message \(m\in R_{p}\), \(a\xleftarrow{\xi}R_{q},e\xleftarrow{\xi}\chi\) is taken as a sample, and the output ciphertext is \(c=(u,v)=(as+pe+m,-a)\).
* \(Dec(sk,c)\to m\): The ciphertext \(c=(u,v)\) is decorpted with the secret key \(sk=s\), and the output \(m=(u+v\cdot sk)\mod p\) is obtained.
* \(Eval((\gamma_{1},\ldots,\gamma_{d}),((c^{(1)},\ldots,c^{(d)})))\to c\): Given \(d\) coefficients \(\gamma_{1},\ldots,\gamma_{d}\in\mathbb{Z}_{q}\) and \(d\) ciphertexts \(c^{(1)},\ldots,c^{(d)}\in(R_{q})^{2}\), the linear homomorphism property is described as follows: \[c = \sum_{i=1}^{d}\gamma_{i}\cdot c^{(i)}=\sum_{i=1}^{d}\gamma_{i} \cdot(u,v)^{(i)}\] (5) \[= (\sum_{i=1}^{d}\gamma_{i}\cdot u^{(i)},\sum_{i=1}^{d}\gamma_{i} \cdot v^{(i)})\] \[= (\sum_{i=1}^{d}\gamma_{i}a\cdot s+\sum_{i=1}^{d}\gamma_{i}pe+ \sum_{i=1}^{d}\gamma_{i}m_{i}\!-\!\sum_{i=1}^{d}\gamma_{i}a)\] \[\rightarrow Enc(sk,\sum_{i=1}^{d}\gamma_{i}m_{i}).\]
## 6 Alternative Methods of Articular Cartilage Diagnosis
### Vibroarthrography (VAG)  
Vibroarthrography is a non-invasive diagnostic method based on the analysis of mechanical vibrations that are generated by a joint during its movement [25; 340; 341]. The movement of the joint surfaces in a healthy joint is smooth, and the vibroacoustic signals generated are minimal. However, in degenerative lesions, characteristic vibrations that are easier to detect are generated [25]. People struggling with OA are characterised by higher amplitude and variability of VAG signals compared to healthy individuals [342; 343]. Through frequency and time analysis of the VAG signals, it is possible to identify char acteristic patterns for different stages of cartilage damage. Vibroarthrography, due to its simplicity, low cost and non-invasiveness, can be used as an effective screening tool for the early diagnosis of OA [34; 344]. VAG is also characterised by its usefulness in both clinical and population-based screening settings, where there is limited access to advanced imaging techniques [34]. Increasingly accurate sensors and the development of analytical systems based on artificial intelligence are influencing the increasing reliability and accuracy of this method.  
Figure 7 shows graphs illustrating vibroarthrography signals recorded during flexion of the healthy knee joint and the knee affected by OA, under two different biomechanical conditions. An open kinematic chain (OCK) and a closed kinematic chain (CKC) were considered. In the two cases mentioned, clear differences in signal characteristics were recorded for the healthy knee joint and the one affected by degenerative changes. The healthy knee joint is characterised by a lower signal amplitude and a more consistent time course, which is related to the smooth sliding of the joint surfaces. In the OA-affected knee, the recorded signals are characterised by higher amplitude and greater irregularity, which is related to increased friction due to unevenness of the articular surfaces as a result of degradation of the articular cartilage.
# Asynchronous Hierarchical Federated Learning Based on Bandwidth Allocation and Client Scheduling
## 4 Simulation Results
### Results  
Figure 3 shows that the proposed approach achieves the best performance, compared to baselines 1 and 2, in terms of model convergence. Specifically, to achieve a certain accuracy (such as 0.9), the proposed asynchronous HFL approach based on bandwidth allocation and client scheduling takes only 33 time units, whereas baseline 1 takes 56 time units and baseline 2 takes 113 time units. Furthermore, the proposed approach can achieve an accuracy of 0.95, which serves as the upper bound of baselines 1 and 2. It is found that the proposed approach can reduce the training time by 70.8% compared to baseline 1, and by 41.1% compared to baseline 2. Moreover, the proposed approach exhibits more stable convergence performance compared to baseline 1. This is because the proposed approach takes into account both the training delay and data quality of the clients.  
Figure 4 presents a similar conclusion to that drawn from Figure 3. Specifically, the proposed approach has a smaller test loss and converges faster, compared to baselines 1 and 2. This is because the proposed approach tends to select the clients that behave well, i.e., the clients with lower delay and higher data quality.  
During the training process, the clients' movements may prevent the clients from uploading model parameters to the corresponding edge server in time. This results in some clients not participating in the edge model aggregation, leading to unstable and poor accuracy performance. The greedy optimization algorithm for uploading model parameters can significantly reduce the uploading delay in an HFL framework. As shown in Figure 5, the horizontal axis represents the normalized time required for the clients to upload their models in existing hierarchical FL methods, and the vertical axis represents the time needed in greedy optimization. However, the greedy algorithm may result in initially allocating clients to a group in one particular area post training. This would cause some  
Figure 4: Test loss over training time.  
Figure 3: Test accuracy over training time.  
edge servers to receive additional clients, potentially leading to uploading congestion. If the bandwidth is not well allocated, the clients will be blocked in the uploading stage, resulting in slow model convergence. However, our proposed algorithm achieves load balancing based on bandwidth allocation and client scheduling, which prevents the occurrence of the above situation.
# Design and Validation of an Adjustable Large-Scale Solar Simulator
## 1 Introduction
[13], with 24 power LEDs and six different wavelengths, obtained a difference under 2% regarding the spectral match compared to natural sunshine. [PERSON] et al. [14] performed theoretical simulations before designing the real model. This is very helpful for investigating the best arrangement of lamps to obtain a proper uniformity. Light sources differ in lifetime, cost, collimation, flux magnitude, and color temperature. The color temperature is an important parameter because it indicates the equivalent blackbody radiator temperature and influences the spectral quality. The reference solar spectrum is provided by the ASTM G173-03 standard [15] at optical air mass AM 1.5. The maximum acceptable deviation over the test area is 15% (ISO 9806) [16]. The sun can be considered as a blackbody radiator at a temperature of approximately 5800 K [17]. A light source with a lower temperature will have a higher energy content in the infrared spectrum and a lower contribution in the visible spectrum (as occurs in tungsten halogen lamps with a color temperature of about 2100-3350 K). Instead, with high color temperatures, the opposite result will be obtained (argon lamps have a color temperature of about 6500 K and a higher energy content in the visible light range). A series of standards [16,18,19,20] defines some parameters which a solar simulator needs to meet, regarding spectral quality, collimation, flux magnitude, and range of obtainable flux. The collimation condition of the simulated solar radiation is satisfied if at least 80% of the irradiance received at any point on the test area has emanated from a region of the solar simulator contained within a subtended angle of 60\({}^{\circ}\) or less. For the flux magnitude, more than 700 W/m\({}^{2}\) is required on the test area, while the permitted deviation should be in the range of \(\pm\)50 W/m\({}^{2}\). This paper presents the design and the validation of an adjustable solar simulator based on 20 metal halide lamps and a parabolic optical system. Nonuniformity and temporal instability tests are investigated in accordance with the IEC 60904-9 standard [21]. Further validation is proposed by characterizing the I-V curve of a PV panel, comparing the results obtained from indoor and outdoor measurements and through a software-implemented numerical model. This paper is organized as follows: in Section 2, the designed solar simulator is presented, regarding the construction, the light source selection, and the optic system utilized; in Section 3, the series of tests is listed with the results obtained; and in Section 4, the conclusions are summarized.
# A Novel Dataset for Multi-View Multi-Player Tracking in Soccer Scenarios
## 2 Related Works
### Methods
#### 2.2.3 Data Association  
Data association can be categorized as either intra-camera or cross-camera data associations.  
Most existing methods address intra-camera data association through either tracklet-to-target or target-to-target matching. In [20; 58], the LSTM network was used to obtain the historical tracklet features, while [PERSON] et al. [18] proposed using the tracklet confidence to measure the performance of each tracklet. Some other methods [19; 24; 26] apply the Kuhn-Munkres algorithm [59] to optimize the assignment problem. [PERSON] et al. [27] proposed a tensor-based high-order graph matching algorithm to flexibly integrate high-order information.  
Various cross-camera data association methods have been proposed to merge single-camera trajectories across different cameras for cross-camera tracking. These methods include assignment methods based on trajectory features such as hierarchical clustering [22; 60; 61; 62; 63], greedy matching [28], multiple hypothesis tracking [25; 64], K-shortest path [65], and camera topology [66]. [PERSON] et al. [28] proposed a Greedy Matching Association (GMA) method that matches local tracklets obtained from different cameras one by one. [PERSON] et al. [66] took camera topology into consideration to reduce the influence of inconsistent appearance and spatio-temporal constraints in different cameras. In contrast to these tracklet-to-tracklet methods, other methods [67; 68] solve the cross-camera tracklet matching problem using tracklet-to-target assignment. For instance, [PERSON] et al. [68] focused on tracklet-to-target assignment and proposed the Restricted Non-negative Matrix Factorization algorithm to compute the optimal assignment solution. Graph-based approaches [68; 69; 70; 71; 72] based on the two-step framework have gradually been adopted by many researchers to solve the data associations across different frames and cameras. Gmcp-tracker [71] utilized Generalized Minimum Clique Graphs to solve the optimization problem of our data association method. Hypergraphs [69] introduced a combined maximum a posteriori (MAP) formulation and a flow graph, which jointly model multi-camera reconstruction as well as global temporal data association. [PERSON] [72] developed a global approach by integrating these two steps via an equalized global graph model.  
Recently, some outstanding works used a deep learning network to replace the graph-model to complete the data association. Reference [73] proposed a self-supervised learning framework to solve the MvMHAT problems. In References [74; 75], the authors built novel networks and achieved end-to-end real-time online tracking. Finally, in [76; 77; 78], the researchers meticulously trained their networks to identify crowds and utilized self-supervision to effectively harness temporal consistency across frames. This allowed them to merge information from multiple perspectives while preserving the accurate location of individuals.