esa-sceva/satcom-chunk-collection huggingface dataset:
# Radio Wave Propagation and WSN Deployment in Complex Utility Tunnel Environments +
## 3 Radio Channel Analysis
### Simulation Results
The RMS DS for the considered utility tunnel environment is depicted in Figure 8. It is the square root of the second central moment of the PDP, defined as [41]:  
\[\sigma_{\tau}=\sqrt{\overline{\tau^{2}}-(\overline{\tau})^{2}} \tag{1}\]  
where  
\[\overline{\tau^{2}}=\frac{\sum_{k}a_{k}^{2}\ \tau_{k}^{2}}{\sum_{k}a_{k}^{2}} = \frac{\sum_{k}P(\tau_{k})\tau_{k}^{2}}{\sum_{k}P(\tau_{k})} \tag{2}\]  
and  
\[\overline{\tau}=\frac{\sum_{k}a_{k}^{2}\ \tau_{k}}{\sum_{k}a_{k}^{2}} = \frac{\sum_{k}P(\ \tau_{k})\tau_{k}}{\sum_{k}P(\tau_{k})} \tag{3}\]  
It must be pointed out that values for \(\overline{\tau}\), \(\overline{\tau^{2}}\) and \(\sigma_{\tau}\) depend on the choice of the noise threshold to process the received power at each delay \(P(\tau)\). The noise threshold used to depict the RMS DS shown in Figure 8 was \(-\)120 dBm, chosen to emulate the typical sensitivity of a ZigBee or LoRaWAN WSN that can be deployed in the tunnel environment. Figure 6: Radiofrequency (RF) power distribution for the XY bidimensional plane at 2-m height for 868 MHz. It is observed that the RMS DS is higher in some areas closest to the center and the final part of the tunnel. This is because of the distribution of the service trays and tubes in the utility tunnel. Each spatial sample of the RMS DS is associated with a PDP. In this specific case, a multipath propagation contribution is higher in the central and final part of the tunnel, but it is necessary to consider all the spatial samples of the environment due to the influence of the topology and morphology of the specific scenario under consideration. Therefore, all the obstacles within the tunnel and the metallic structure of the service trays play an important role in the multipath propagation. In order to have knowledge of the frequency domain channel description, the coherence bandwidth (CB) was obtained from the RMS DS for the considered scenario. The CB can be defined as the bandwidth over which the frequency correlation function is above 0.9; then, the CB is approximately \(B_{c}\approx 1/50\sigma_{\tau}\); see [41]. Figure 9 shows the CB for the considered utility tunnel showing values that vary from 0.01 to 0.6 MHz. It can be seen that the lowest values of RMS DS cause higher values of CB. Therefore, a receiver in those areas can encounter higher multipath interference. Figure 8: Root mean square delay spread (RMS DS) estimation within the utility tunnel for 2-m height for 868-MHz frequency. Figure 7: Power delay profile at a given cuboid located at the center (60 m, 1 m and 2 m) at 868-MHz frequency.
## 3 Results
### Real-Life Training  
Real-life wheelchair skills training can vary in nature, and often consists in completing tasks within controlled environments, such as obstacle courses, and measures speed and time completion to assess improvement [15]. Other methods, though less popular, are 'ecological' in nature where the user drives through real environments, while also interacting with them, such as schools and homes [15]; the interactions can mimic what someone would do daily like reaching for objects, writing, and opening doors [15]. Due to the heterogeneity of real-life trainings, a way to standardise them has been developed that is called the wheelchair skills training programme (WSTP) [21]. This programme can be used for manual and powered WUs and mobility scooters. The programme consists of a set of tasks that a person needs to successfully complete to be deemed able to drive a wheelchair independently. Specifically, it tests the WUs on individual tasks (e.g., driving forward, backward, through obstacles, and turning), with the aim of teaching users to deal with various real-life situations such as going shopping [21].  
The efficacy of the WSTP was analysed by [PERSON] et al. [23] who reviewed 10 randomised controlled trials (RCTs), and 7 non-RCTs to analyse the short-term and long-term retention of skills following WSTP. In the RCTs, participants undergoing the WSTP showed higher improvement in the short-term (immediately to one-week after) retention of skills than those undergoing other methods, for manual WUs. For long-term effects (after 3-12 months), instead, no significant difference was noticed compared to other training methods. In non-RCTs, instead, manual WUs undergoing the WSTP showed better improvement within 5 weeks as compared to other methods. Although the results show the effectiveness of the WSTP for short- and medium-term improvement of skills of manual Wus, insufficient evidence was reported for powered WUs as not enough studies reviewed by the authors investigated the effects of the WSTP in the acquisition of driving skills. A similar review was conducted by [PERSON] et al. [22], who reviewed 13 RCTs that used the WSTP to train manual and powered WUs, as well as mobility scooters. [PERSON] et al. concluded that the WSTP has a meaningful effect on the improvement of skills compared to no training or other methods [22]. Furthermore, in addition to being an effective training method, the WSTP consists in performing tasks in a safe and controlled environment, thus allowing WUs to be more confident during the training [22].  
It must be stressed that the WSTP rarely contains tasks that mimic real-world driving experiences such as driving in different environments and interacting with them [15]. Importantly, real-life training requires a lot of time and resources which are not available to everyone [24]. Powered wheelchairs are also heavier than manual ones, and can go at moderately high speeds, thus incidents during real-life training can be very harmful and therefore training must be conducted in a careful manner.
## 5 Treatment Results and Discussion
Meanwhile, the maxillary molars also showed an intrusion by 2 mm without significant mesial movement resulting in a flattened occlusal plane [1]. The maxillary total arch intrusion resulted in rotation of the mandible, which induced comfortable lip closure and a favorable profile. [PERSON] et al. [13] also reported a case in which APLR with TSADs was applied in a skeletal Class II patient with a hyperdivergent pattern showing a gummy smile. As a result of treatment, bodily retraction and intrusion of the incisors, total intrusion of the maxillary dentition, and mandibular autorotation were achieved. The gummy smile was resolved by extensive anterior retraction and intrusion with proper torque control [13]. [PERSON] et al. reported two cases in which APLR was applied to a skeletal Class II patient with a hyperdivergent pattern, but autorotation occurred differently. In the first case, the maxillary incisors showed bodily retraction and intrusion, and the molars were intruded by 1.5 mm, which resulted in mandibular counterclockwise autorotation and the anterior positioning of Pogonion by 1.6 mm [5]. In the second case, the maxillary incisors showed controlled tipping, with intrusion by 4 mm and retraction by 7 mm. The maxillary molar intrusion was 1.5 mm. However, no autorotation was observed, contrary to other cases [5]. This may result from mandibular repositioning after resolving of the CO-CR discrepancy [5]. Next, considering the effect of APLR on periodontal tissue, despite the significant amount of retraction, the alveolar bone around the incisors did not show vertical bone loss [5]. APLR showed similar results to the conventional appliances for alveolar bone loss in the palate; however, significantly smaller vertical alveolar bone loss was found when APLR was used. This is because, regardless of the type of lingual retractor, the anterior teeth are splinted together [34; 37; 38]. Finally, there have been no reports on the long-term stability of APLR with TSADs. However, in a case report by [PERSON] et al., stable occlusion and periodontal health were shown after a retention period of one year [13]. The treatment stability using APLR is expected to deliver results similar to the long-term stability of intrusion and en-mass retraction. This necessitates future studies on the long-term stability of lingual retractors.
# Experimental Verification of Yam (_Dioscorea rotundata_) Drying with Solar Adsorption Drying
## 2 Materials and Methods
### Temperature, Air Velocity and Weight Measurements  
Calibrated K-type thermocouples were used to measure the inlet and outlet air temperature of all the units in Figure 2, logged by an Agilent 34970A data logger (Agilent, Santa Clara, CA, USA). An analytical balance (Ohaus, Model PA-2102, Parsippany, NJ, USA) with precision 0.01 g was used to weigh the drying samples. This was done manually with a 30 minute-interval for the first two hours and one-hour interval until the end of drying by removing the samples from the drying chamber. The samples were placed back into the drying chamber no later than five minutes to ensure continuity of the drying process. The air velocity was measured from time to time to ensure it had an average constant with a thermal anemometer (Testo, model 425, Lenzkirch, Germany, accuracy \(\pm\) 0.05 m/s) by placing the rod housing the sensor perpendicular across the direction of the airflow for both SD and SAD. Each time, three measurements were performed and the values were averaged. The location of temperature measurements is shown in Figure 2. For the comparison of the drying behavior of different cultivars the moisture ratio is used:  
\[MR(t)=\frac{M(t)}{M_{start}} \tag{1}\]  
where \(MR(t)\) is the moisture ratio at time, \(t\), \(M(t)\) is the moisture content at time \(t\), and \(M_{start}\) is the initial moisture content.
## 3 Applications to Communication Network Design
### Overview of Selected Papers
#### 3.2.2. Models That Use as Auxiliary Resolution Procedures Shortest Path Dedicated Algorithm(s)  
Herein, we refer to representative works describing multicriteria routing models of various types and for different network environments where the resolution approach uses, as auxiliary resolution procedures, algorithms dedicated to single objective or multiobjective path problems. A summary of some essential features of these models is in Table 5.  
Paper [173] develops a stochastic multiple-objective dynamic routing model for circuit-switched networks such that the routes for all node-to-node traffic flows may change dynamically. The objective functions of the network-wide optimization model are the mean blocking probability and the maximal node-to-node blocking probability. The resolution method of the model is heuristic, but for calculating candidate paths, blocking probabilities and implied costs [174] are used, leading to a specific auxiliary-constrained biobjective shortest path problem. This is solved exactly with a modified version of the biobjective shortest path algorithmic approach in [41], enabling us to select the paths that are candidates to be efficient. A stochastic hierarchical bilevel multiobjective routing model for MPLS networks with two service classes including fairness objectives is described in [175]. A heuristic resolution method for this complex model is proposed and tested in a reference network which is based on an auxiliary biobjective shortest path sub-model for calculating candidate paths. This sub-model uses'marginal implied costs' (as proposed in [176]) and blocking probabilities and is solved exactly by the method in [41]. The authors in [133] propose a multiobjective RWA routing model for Elastic Optical Networks with spectrum segmentation and shared backup protection (meaning that the bandwidth of a backup path may be shared by several active paths) that seeks to optimize blocking probability and fault restoration ratio. The resolution approach is a metaheuristic, a Deep Neural Network model with a multiobjective Fuzzy Inference System which recurs to [PERSON]'s \(k\)-shortest path algorithm, and its performance is compared with similar calculation procedures. The work in [177] proposes a biobjective extension of the shortest path-based routing principle largely used on the Internet and, in general, in shortest path-based routing networks, namely in the context of extensions of the application of link state routing protocols such as OSPF. It considers traffic splitting according to an equal cost multipath (ECMP) split rule and that the paths are calculated with a single objective shortest path algorithm, the weights of which have to be optimized in order to obtain approximate efficient solutions of a biobjective network optimization model. The two OFs of this model are traffic load balancing functions in fully operational and in arc-failure scenarios.
# Performance-Enhancing Sulfur-Doped TiO2 Photoanodes for Perovskite Solar Cells
[PERSON]
1 Solar Energy Research Institute (SERI), Universite Kebangsam Malaysia (UKM),  
Bangi 43600, Selangor, Malaysia; [EMAIL_ADDRESS] (M.A.M.M. ;) [EMAIL_ADDRESS] (M.S.J. ; [EMAIL_ADDRESS] (M.A.M.T. ); [EMAIL_ADDRESS] (M.F.M.N.N. ); [EMAIL_ADDRESS] (M.A.M.T. ); [EMAIL_ADDRESS] (M.F.M.N.N. ); [EMAIL_ADDRESS] (M.A.M.T.) [PERSON]
1 Solar Energy Research Institute (SERI), Universite Kebangsam Malaysia (UKM),  
Bangi 43600, Selangor, Malaysia; [EMAIL_ADDRESS] (M.A.M.M. ;) [EMAIL_ADDRESS] (M.S.S. ); [PERSON]DDRESS] (M.S.J. ; [EMAIL_ADDRESS] (M.A.M.T. ); [EMAIL_ADDRESS] (M.F.M.N.N. ); [EMAIL_ADDRESS] (M.A.M.T. ); [EMAIL_ADDRESS] (M.F.M.N.N. ); [EMAIL_ADDRESS] (M.A.M.T.) [PERSON]
1 Solar Energy Research Institute (SERI), Universite Kebangsam Malaysia (UKM),  
Bangi 43600, Selangor, Malaysia; [EMAIL_ADDRESS] (M.A.M. ;) [EMAIL_ADDRESS] (M.S.J. ; [EMAIL_ADDRESS] (M.A.M.T. ); [EMAIL_ADDRESS] (M.F.M.N.N. ); [EMAIL_ADDRESS] (M.A.M.T. ); [EMAIL_ADDRESS] (M.F.M.N.N.N. ); [EMAIL_ADDRESS] (M.A.M.T. ); [EMAIL_ADDRESS] (M.F.M.N.N. ); [EMAIL_ADDRESS] (M.A.M.T. ); [EMAIL_ADDRESS] (M.F.M.N.N. ); [EMAIL_ADDRESS] (M.A.M.T. ); [EMAIL_ADDRESS] (M.F.M.N.N. ); [EMAIL_ADDRESS] (M.A.M.T. ); [EMAIL_ADDRESS] (M.F.M.N.N.N. ); [EMAIL_ADDRESS] (M.A.M.T. ); [EMAIL_ADDRESS] (M.F.M.N.N. ); [EMAIL_ADDRESS] (M.A.M.T.) [PERSON]
1 Solar Energy Research Institute (SERI), Universite Kebangsam Malaysia (UKM),  
Bangi 43600, Selangor, Malaysia; [EMAIL_ADDRESS] (M.A.M.T. ; [EMAIL_ADDRESS] (M.S.J. ; [EMAIL_ADDRESS] (M.A.M.T. ); [EMAIL_ADDRESS] (M.  
Metal doping of TiO\({}_{2}\) has become a practical technique to modify the band position and improve the thin film conductivity to fabricate photo-anodes with high charge extraction capacity. Dopants, such as yttria, niobium, magnesium and tin, have been proven to enhance the overall PSC efficiency due to the enriched layer conductivity and high electron mobility [11; 12; 13; 14]. Although many dopants have been used to modify the TiO\({}_{2}\) photoanode for PSCs, the application of sulfur as dopant for these cells has not been reported yet. S-doped TiO\({}_{2}\) has been demonstrated to enhance photocurrent, light absorbance and photocatalytic activity and modify the band gap energy in other applications, such as coatings and photo-catalysis [15; 16]. These properties could improve the characteristics of the photo-anode thin films for perovskite solar devices. In this study, sulfur was used for the first time as dopant in the TiO\({}_{2}\) photo-anode thin film in solid-state planar heterojunction solar cells. Methylammonium lead iodide (CH\({}_{3}\)NH\({}_{3}\)PbI\({}_{3}\)) was used as the light absorber and spiro-OMeTAD as HTL. The effects of charge extraction and blocking of holes from the TiO\({}_{2}\) mesoporous layer was eliminated by choosing a planar PSC architecture. A sol-gel solution containing sulfur and titanium salts was spin coated onto the FTO glass to form the S-doped TiO\({}_{2}\) photo-anode thin film. The doping concentration of sulfur is tuned by controlling the sulfur salt content in the sol-gel solution.
# CNN-Based Multi-Factor Authentication System for Mobile Devices Using Faces and Passwords
## 4 Experimental Results and Discussion
### Discussion  
Equal information amount of three factors: The scientific importance of this study is reflected in the fact that, while the authentication accuracy was increased to over 99% when using three factors, the weight of each factor was also equal. As fake face images can be used to pass a face authentication system, the highest level of security can be applied when using three or more factors. To prove that the security level has increased, it must be confirmed that each element of the multi-factor system has an equal influence on the accuracy of authentication. In this study, the equal influence of each element was proven through FAR testing using fake information. When a password made of text was transformed into a black-and-white image for learning, the FAR value was 0.98 if the password was fake. This indicates that the amount of password information is small enough to be ignored, and identity was confirmed only with face and auxiliary image information. In the case of fake faces and fake auxiliary images, the FAR value ranged from 0.2 to 0.3, as shown in Figure 9. The problem was solved by converting the black and white image of the password into a color image, then combining the password color image with a different image mask for each user with a weight of 0.5. Figure 8 indicates equal FAR values, showing that the information amount of the password image, face image, and auxiliary image have similar weights for identification. This process completes the STP algorithm and allows for the creation of a secure password image. Applicability for mobile devices: The CNN structures studied for use in mobile devices include MobileNet [50] and ShuffleNet [51]. However, MobileNet has a 28-layer structure, and parallel processing is performed through depthwise convolution, while ShuffleNet has an 11-layer structure and uses the Channel Shuffle method. When testing multi-input multi-factor authentication using these two structures, their structures were considered somewhat complicated. In order to test the influence of each factor, Alexnet [52] was selected as a standard architecture, which has a relatively simple structure and a low number of layers (i.e., eight layers), and, therefore, the first experiment used a CNN with an eight-layer structure. Afterward, MMCNN with a lighter (four-layer) structure was proposed, which was experimentally confirmed to have an accuracy of 99.6%. The number of parameters in the proposed CNN structure was 86,067,556 with eight layers and 13,717,220 with four layers, and the memory capacity occupied when run on a 64-bit computer was 657 megabytes with eight layers and 105 megabytes with four layers.
# Analysis of the Dihedral Corner Reflector's RCS Features in Multi-Resource SAR
## 2 The RCS Calculation Model for Dihedral CR  
### The Standard RCS Model of Dihedral CR  
The RCS characterizes the energy of a ground target for scattering the radar signal, which can be calculated using the following formula:  
\[\sigma=\frac{4\pi\cdot S_{e}^{2}}{\lambda^{2}} \tag{1}\]  
where \(\lambda\) represents the radar wavelength and \(S_{e}\) denotes the radar effective scattering area.  
For the RCS calculation of an ideal triangular CR and dihedral CR, there are standard calculation formulas in radar applications [8; 20]. They assume that the CR axis is aligned with the incident direction of the SAR signal. However, due to the different incident angles of multi-SAR satellites, when the corner reflector adapts to the incident angle of one satellite, its axis would deviate from the incident angle of other satellites. This paper proposes a model for estimating the RCS reduction caused by the deviation between the incident angle and the CR's axis, without considering the influence of the panel's dielectric constant [25; 26].  
Taking the dihedral CR with a square panel of side length L as an example, when the CR axis coincides with the radar incident light, its theoretical RCS calculation formula is as follows [8]:  
\[\sigma_{D}=\frac{8\pi L^{4}}{\lambda^{2}} \tag{2}\]Figure 1b shows the three-dimensional schematic diagram of the effective scattering area, and the corresponding cross-section is shown by the green dotted line in Figure 1a.
## 4 Results and Discussion
### Loop 6 Escalation of Congestion and Loop 7 Balancing of Dynamic Access  
The Loop 6 Escalation of Congestion from Restrictions explores the consequences of temporal parking restrictions, highlighting how a reduction in available delivery time can trigger a negative spiral. The increasing pressure to maximize the number of deliveries within a limited period can lead, in the absence of adequate business efficiency improvements, to an increase in circulation time and congestion, further increasing the time spent parking and reducing the effective delivery time. However, it is crucial to consider that this pressure induced by restrictions can also push companies to adopt more efficient operational strategies (route optimization, faster loading/unloading), potentially mitigating the negative impacts on traffic.  
In contrast, the Loop 7 Balancing of dynamic access describes a balancing mechanism centered on the implementation of dynamic access measures to parking areas. Effective dynamic management aims to reduce the time spent parking, thereby increasing the effective time available for delivery operations. This increase in operational time can potentially translate into a greater number of deliveries and, in the long term, a reduction in the overall circulation time of commercial vehicles and urban congestion. The loop self-regulates as increased congestion can stimulate the adoption of further dynamic parking management measures, creating positive feedback towards a more efficient and less congested logistics system. The interaction between these two loops suggests that the system's response to restrictions is complex and depends on the ability of companies to innovate their operations,  
Figure 6: Loop 6 Escalation of congestion from restrictions (Negative reinforcing loop) and Loop 7 Balancing of dynamic access (Balancing loop).  
while targeted interventions in parking management offer significant potential to improve urban fluidity.
# Formal Modeling and Improvement in the Random Path Routing Network Scheme Using Colored Petri Nets
## 2 Related Work
### Source-Location Privacy Addressing Scheme
#### 2.2.1 Fake Source Routing  
The baseline of fake source routing (FSR) was introduced by [12]. It is one of the very first schemes for source-location privacy in WSNs. FSR works by using a set of fake source nodes as a natural source, which can act as a decoy. The mechanism of a fake source is that it generates fake nodes to engineer the network traffic to confuse an adversary that these fake packets are actual packets. Fake packets are encrypted and have the same length, making it difficult for the adversary to differentiate between genuine and fake packets. These fake nodes are carefully positioned to avoid leading adversaries towards the actual source [13]. Two strategies exist that form the baseline for fake source routing. (1) persistent fake source routing, and (2) short-lived fake source routing [14; 15]. Short-lived fake source routing is an injection strategy, and it does not require any additional overhead.  
This scheme is easy to implement, but it provides poor privacy levels, as the fake sources are short-lived. A fake packet guides an adversary in the direction where there is no source code and makes it easy for the adversary to catch basic packages. A persistent fake routing scheme is also similar to a short-fake source, but the point is that only one artificial node is not enough to distract an adversary. So, for this reason, the constant fake source, once it decides to become a phony source, regularly generates bogus packets so that the adversary can effectively be determined.