esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussions
However, the differences between the values obtained for the two scenarios are less than in SSIM. This may be because the range covered by UIQI values is wider. Because UIQI can be used with a color-sensitive approach, it can be used more efficiently to colorize grayscale aerial photographs. Compared to Bhattacharyya, it was determined that UIQI can be used in the evaluation of enhanced grayscale aerial photographs. Considering all test photographs, it was found that the Bhattacharyya measure was not sensitive enough to the current dataset, despite the fact that both metrics produced favorable findings. Lower Bhattacharyya distance values were obtained in some of the images where the smoothing effect was more prominent, with \begin{table}
\begin{tabular}{c c c} \hline \hline
**Quality Metric** & **Dataset-1** & **Dataset-2** \\ \hline RMSE & 5.46 & 5.87 \\ PSNR & 33.40 & 32.80 \\ SSIM & 0.8714 & 0.8604 \\ UIQI & 0.9143 & 0.9070 \\ BHATTACHARYYA & 0.023 & 0.026 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Average values based on quality metrics. the exception of the test images provided as examples. In this scenario, lower metric distances suggest a greater similarity between the two images. Furthermore, it is currently not feasible to effectively assess this metric in historical aerial pictures due to the fact that the distance values fall within a relatively limited range.
## Providing IoT Services in Smart Cities through Dynamic Augmented Reality Markers  
**[PERSON] 1,*, [PERSON] 1, [PERSON] 2, [PERSON] 1, [PERSON] 1, [PERSON] 2, [PERSON] 2 and [PERSON] 1**  
1 AtlantTIC, Universidade de Vigo, Rua Maxwell S/N, 36310 Vigo, Spain; E-Mails: [EMAIL_ADDRESS] (A.P.-R.); [EMAIL_ADDRESS] (F.J.G.-C.); [EMAIL_ADDRESS] (P.S.R.-H.); [EMAIL_ADDRESS] (E.C.-M.)  
2 Galician Research and Development Center in Advanced Telecommunications (GRADIANT), Edif. CITEXVI local 14, Campus Universitario de Vigo, 36310 Vigo, Spain; E-Mails: [EMAIL_ADDRESS] (D.G.-C.); [EMAIL_ADDRESS] (O.P.-G.); [EMAIL_ADDRESS] (F.G.-C.)  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS].  
Academic Editor: [PERSON]  
_Received: 21 April 2015 / Accepted: 25 June 2015 / Published: 3 July 2015_  
**Abstract:** Smart cities are expected to improve the quality of life of citizens by relying on new paradigms, such as the Internet of Things (IoT) and its capacity to manage and interconnect thousands of sensors and actuators scattered across the city. At the same time, mobile devices widely assist professional and personal everyday activities. A very good example of the potential of these devices for smart cities is their powerful support for intuitive service interfaces (such as those based on augmented reality (AR)) for non-expert users. In our work, we consider a scenario that combines IoT and AR within a smart city maintenance service to improve the accessibility of sensor and actuator devices in the field, where responsiveness is crucial. In it, depending on the location and needs of each service, data and commands will be transported by an urban communications network or consulted on the spot. Direct AR interaction with urban objects has already been described; it usually relies on 2D visual codes to deliver object identifiers (IDs) to the rendering device to identify object resources. These IDs allow information about the objects to be retrieved from a remote server. In this work, we present a novel solution that replaces static AR markers with dynamic markers based on LED communication, which can be decoded through camerasembedded in smartphones. These dynamic markers can directly deliver sensor information to the rendering device, on top of the object ID, without further network interaction.  
Keywords:Internet of Things; sensors; augmented reality; smart city; visible light communication +
Footnote †: journal: Journal of Sensors
# Synchronous Machine Winding Modeling Method Based on Broadband Characteristics
###### Abstract  
The accurate establishment of the equivalent circuit model of the synchronous machine windings' broadband characteristics is the basis for the study of high-frequency machine problems, such as winding fault diagnosis and electromagnetic interference prediction. Therefore, this paper proposes a modeling method for synchronous machine winding based on broadband characteristics. Firstly, the single-phase high-frequency lumped parameter circuit model of synchronous machine winding is introduced, then the broadband characteristics of the port are analyzed by using the state space model, and then the equivalent circuit parameters are identified by using an optimization algorithm combined with the measured broadband impedance characteristics of port. Finally, experimental verification and comparison experiments are carried out on a 5-kW synchronous machine. The experimental results show that the proposed modeling method identifies the impedance curve of the circuit parameters with a high degree of agreement with the measured impedance curve, which indicates that the modeling method is feasible. In addition, the comparative experimental results show that, compared with the engineering exploratory calculation method, the proposed parameter identification method has stronger adaptability to the measured data and a certain robustness. Compared with the black box model, the parameters of the proposed model have a certain physical meaning, and the agreement with the actual impedance characteristic curve is higher than that of the black box model.  
single-phase high-frequency lumped parameter model; optimization algorithm; state space; common mode and differential mode impedance +
Footnote †: journal: Applied Sciences
## 3 Experiments Results and Discussion
### Impact of the Factor \(\lambda\) in Weighted Distance Transform  
To verify the effectiveness of combining the two distance transforms, we compared the single interaction results when \(\lambda\) took different values. Different values represent the different weights of the two distance transforms. The weighted distance became Euclidean distance completely when \(\lambda\) took 0, and Geodesic distance completely when \(\lambda\) took 1. However, we used the same user interactions during the experiment.  
As can be seen from Table 1, the interactive segmentation method performed much better than the conventional automatic segmentation method U-net, by as much as 10%. Our method with the parameter \(\lambda=0.5,~{}\mathcal{L}_{\text{total}}\) achieved a dice score of 94.45 \(\pm\) 3.26% and it performed better than the other four values of \(\lambda\). By fixing the loss function to be \(\mathcal{L}_{\text{total}}\), we can see that the results when \(\lambda\) was t between 0 and 1 were better than both 0 and 1. This proved that combining the two distance conversions can perform better than using either method alone on an interactive segmentation task.  
Figure 6 shows a comparison of the segmentation results of our method with different values of \(\lambda\) by given the same user interaction points. The upper case 1 is a tumor with an obscure border, where the interaction point location information is more important than the texture information. In this case, the performance of Euclidean distance transform should be better than Geodesic transform, which is as the same in Figure 6. In the lower case 2, the tumor boundary is obvious, but it has a mis-segmentation outside the tumor. This requires both texture information to ensure correct segmentation of the tumor region and interaction point location information to instruct the network to remove mis-segmented regions outside the tumor. Therefore, \(\lambda\) of 0.5 is better than any other value in case 2. This proves that the combination of our two distance transforms is beneficial in dealing with tumors in different cases.  
The combination of Euclidean distance transform and geodesic distance transform can both convey the location information of interaction points and make use of image context information. The experimental results demonstrate that this combination improves the stability of the segmentation model to cope with images that are difficult to segment.
## 4 Efficient FFT Algorithms
### Traced FFT Pruning  
[PERSON] _et al_. [68] proposed a generic FFT pruning technique for the applications where the required outputs are very sparse. For example, in spectrum sensing one might be interested in sensing the spectrum corresponding to certain bins of the FFT or in narrow frequency bands. The proposed traced FFT pruning (TFFTP) technique does not require the outputs to be in continuous windows and thus can be applied for such spectrum sensing applications. A simple and effective method has been proposed to trace the computation path for the required outputs. For an \(N\)-point FFT computation there are \(s=\log_{2}N\) stages in the signal flow graph. Initially the output nodes of the last stage are labeled from 0 to \(N-1\). The output nodes of \((s-1)^{\text{th}}\) stage are divided into two groups and the nodes in each group are labeled from 0 to \(N/2-1\). The procedure is repeated until the first stage, where the nodes are divided into \(N/2\) groups and the output nodes of each group are labeled from 0 to 1. Using the labels of the desired output nodes of the last stage, a bin set \(\psi_{s}\) is formed. Other sets are derived iteratively as: \(\psi_{s\text{-}1}=\psi_{s}\%\) (\(N/2\)), \(\psi_{s\text{-}2}=\psi_{s\text{-}1}\%\) (\(N/4\)), and so on until \(\psi_{1}\) is obtained, where \(\%\) is modulo operation. The sets \(\psi_{1}\), \(\psi_{2}\), \(\ldots\), \(\psi_{s}\) are the desired output node sets for the butterflies of stage 1 through stage \(s\) respectively.  
All the nodes on the signal flow graph are first labeled and the flow lines leading to the desired output nodes are joined to yield the computational path. Only the butterflies that lead to the desired output nodes in each stage are executed. The TFFTP technique can be applied to input pruning and also to simultaneous input and output pruning.
# A Proposal of a Troposphere Model in a GNSS Simulator for VANET Applications
## 2 Related Work  
Many works exist in the literature about GNSS software receivers. Starting from the GPS Standard Positioning Service, new systems have been proposed able to provide global coverage including GLONASS, Galileo and other regional satellite navigational systems, as described in Section 3. Many of these works concern software and hardware simulators with the aim of perform navigation tests in a secure and repeatable way.  
Figure 1: Global Navigation Satellite System (GNSS) in a Vehicular Ad-Hoc Network (VANET) scenario.
aquatic lifeforms [11,12]. They are applied to environmental monitoring systems to equip expert biologists in the underwater domain, such as ichthyologists, with vital data and information to make informed decisions concerning environmental measures to preserve and protect the aquatic biodiversity and its ecosystems [11, 12, 13].  
Over 900 underwater species and families of living organisms communicate via acoustic expressions and cues [1,3,14, 15, 16] in the range from 10 Hz to over 100 kHz [14, 15, 16], which includes mammals, fishes, and invertebrates [1,3, 14, 15, 16, 17]. In addition to acoustics, other signal types are used by aquatic organisms [3,18,19]. Species like plankton use optical communication in the form of bioluminescence [18]. Furthermore, an African freshwater fish group called mormyridae uses both acoustic and electrical signals in social interactions and for spacial orientation [19]. Anthropic emissions in aquatic environments cause negative footprints, which pose a serious threat to their inhabitants [1,3]; for example, fish and invertebrates have been reported to exhibit Deoxyribonucleic Acid (DNA) damage and reduced egg production due to noise pollution [1]. The vitality of communication for both humans and living organisms in the underwater medium is evidenced in this article, which endorses a symbiotic co-existence between humans and nature. A balanced co-existence is mutually beneficial for the survival of both parties [20].  
The main contributions of this article are (i) benchmarking various wired and wireless underwater communication systems and comparing their advantages and disadvantages; (ii) highlighting and discussing the negative impacts of anthropogenic emissions from communication systems on aquatic lifeforms; and (iii) demonstrating the importance of underwater communication technologies, such as remote sensing and passive monitoring, in preserving biodiversity and ecosystems. The structure of the article is as follows: Section 2 covers the underwater ecosystems and biodiversity; the types of underwater communication are discussed in Section 3; the applications of sensor network modalities in Section 4 cover the sensors network modalities and applications; and the conclusions and future directions are discussed in Section 5.
## 3 Asset Localization
### 5g  
5G is a cutting-edge mobile technology, which supports on site installations besides large-scale infrastructure. In the 5G standard, great effort was made to improve the positioning capabilities of the previous LTE standard; since Release 17, IIoT localization has become an important topic of the standard [80]. 5G provides time- and angle-based positioning, and the variable parameters of the NR (New Radio) interface help to improve the accuracy of 5G positioning (e.g., higher bandwidth, variable subcarrier spacing, different antenna patterns, etc.).  
While 5G supports different kinds of localization methods, these are mainly geometrical or closed-form solutions. However, a couple of works, which aim to improve the accuracy of the localization using machine learning methods, can be found--mainly concerning an IIoT environment, i.e., in indoor situations. One typical positioning method is \"fingerprinting\", which is based on readily observable radio channel properties, such as the receive signal strength (RSSI). To improve the accuracy of such solutions, ref. [81] tries to estimate and correct the error of the location using different machine learning models. To estimate the position, the kNN technique and vanilla neural networks were compared. Targeting the same problem, ref. [82] compares kNN- and SVR- (Support Vector Regression) based techniques to the defined DELTA method, which implements a dense neural network to infer the position from RSSI measurements.  
A more sophisticated method in 5G localization is angle-based positioning. Using beamforming, the technique in [83] samples the received PDPs (Power Delay Profile),creates beamformed fingerprints and uses trained temporal convolutional neural networks (TCN) and LSTM networks to infer the location from the beamformed fingerprint. The TCN network is capable of tracking the location with an accuracy of a couple of meters on average. The solution has low energy consumption, even compared to GPS systems. Also using deep neural networks, ref. [84] optimizes the handover process by improving 5G localization based on beamforming. The solution's accuracy proved to be 1.25 m on average.  
A comprehensive study on 5G and positioning can be found in [85], where a couple of methods--including machine learning-aided localization methods--are compared and introduced.
# Critical Review of Basic Methods on DoA Estimation of EM Waves Impinging a Spherical Antenna Array
## 3 Mathematical Formulations
### Analysis of the Space Domain
\begin{array}{rcl}\mathbf{p}(k)=\left[\begin{array}{c}p_{1}(k)\\ \vdots\\ p_{I}(k)\end{array}\right]&=&\sum\limits_{u=1}^{U}\left[\begin{array}{c}h_{1,u}(k)\\ \vdots\\ h_{I,u}(k)\end{array}\right]s_{u}(k)+\left[\begin{array}{c}n_{1}(k)\\ \vdots\\ n_{I}(k)\end{array}\right]\\ &=&[\mathbf{h}(\Omega_{1}),\ldots,\mathbf{h}(\Omega_{U})][\mathbf{s}_{1}(k),\ldots,s_{U} (k)]^{T}+\mathbf{n}(k)\\ &=&\mathbf{H}(\mathbf{\Omega})\mathbf{s}(k)+\mathbf{n}(k)\end{array}  \tag{11}\]  
\(\mathbf{\Omega}=[\Omega_{1},\ldots,\Omega_{U}]\) is the set of all unknown DoAs. The signals and noise are assumed to be zero-mean complex Gaussian processes, i.e., [25]  
\[E\Big{\{}\mathbf{s}(k)\mathbf{s}^{H}(k)\Big{\}}=\mathbf{R}_{\rm ss}(k)\text{ and }E\Big{\{}\mathbf{n}(k)\mathbf{n}^{H}(k)\Big{\}}=\sigma^{2}\mathbf{I} \tag{12}\]  
where \(E\{\cdot\}\) is the expectation, and \(\left(\cdot\right)^{H}\) is a Hermitian matrix transpose. This results in the following covariance matrix of the array [31]:  
\[\mathbf{R}_{pp}(k)=E\Big{\{}\mathbf{p}(k)\mathbf{p}^{H}(k)\Big{\}}=\mathbf{H}(\mathbf{\Omega})\mathbf{ R}_{\rm ss}(k)\mathbf{H}^{H}(\mathbf{\Omega})+\sigma^{2}\mathbf{I} \tag{13}\]  
The assumption of a Gaussian signal in free space is not necessarily true. That is, a signal with a single frequency in a short time window can possibly be deterministic in nature instead of random. The deterministic model of the array covariance matrix is presented in Section 4.5.
# Development and Evaluation of Doppler Ultrasound Training Phantom for Human Vessel Simulation
###### Abstract  
The purpose of this study was to create a Doppler ultrasound training phantom aimed at aiding beginners in comprehending and effectively utilizing critical parameters during the learning process. Our designed training phantom does not require the use of a water pump or an automated injector. The fabrication of the vessel-mimicking phantom was accomplished using agarose gel. We utilized LEGO blocks to introduce a height difference that simulated blood flow within the phantom. The imitation blood material was prepared using glycerin. Ultrasound images were obtained using an Accuvix V10 device. This study utilized a Doppler ultrasound training phantom to facilitate stable imaging for beginners during scanning, due to its secure fixation. Furthermore, the fabricated vessel-mimicking phantom offers the advantage of adjusting the diameter of vessels during the fabrication process. Additionally, the easy adaptability, to tailor the phantom specifically for certain conditions by modifying only the vascular components, is another notable advantage. The experimental values for parameters such as the color box, scale, and color gain were collected. The spectral Doppler was used for a rough assessment of blood flow velocity. Color Doppler images, acquired via adjusting the color box to the left and right, displayed blood flow information in blue on the left, and red on the right. At a scale setting of 4 kHz and 0.6 kHz for color Doppler imaging, aliasing was absent at 4 kHz, but appeared at 0.6 kHz. Experiments involving various gain settings (2 dB, 5 dB, 10 dB, 35 dB, 60 dB, and 100 dB) demonstrated that the blood flow information was diminished at 2 dB, and exaggerated at 100 dB.  
Doppler ultrasound training phantom; color Doppler; color box; scale; color gain
## 3 Security and Privacy Challenges
### Intrusion Detection System
#### 3.4.1 Signature-Based Intrusion Detection System (SIDS)  
SIDS, also known as knowledge-based detection or misuse detection, works on a pattern matching technique to find similar known attacks in the past. An intrusion signature is matched with a database of previously known signatures, and an alarm is raised in the event of a match. In SIDS, host's logs are compared to identify sequences of commands or actions which have previously been identified as malware [178]. Techniques used for generating signatures for SIDS include state machines, formal language string patterns, or semantic conditions. Traditional SIDSs match network packets against a database of signatures and are unable to identify attacks that span over numerous packets. Also, \"zero-day\" attacks have left SIDS techniques less effective, as there is no prior signature for such attack types. Also, polymorphic malware frequently changes its identifiable characteristics and undermines the adequacy of the SIDS traditional approach [186]. The authors of [187]  
Figure 13: IDS classification.  
reported the detection ability of SIDS against web-based Uniform Resource Identifier (URI) attacks. Three open-source SIDS, i.e., Snort, ModSecurity, and Nemesida, were tested against seven attack datasets using predefined rulesets. The results revealed that untuned SIDSs with the least sensitive configurations were able to detect only 6-8% of attacks, while the most sensitive ones achieved 73-83% with a much lower precision rate of 0.015, thus generating impractical alert volumes.  
The researchers have deployed classification models using supervised ML techniques and used a Naive Bayes algorithm-based characterization approach in the probability estimation using network data traffic characteristics. The Naive Bayes algorithm can detect DDoS, DoS, and Code injection attacks on KDD CUP 1999+NSL, UNSW-NB15 datasets. Decision trees are implemented on CICIDS 2017, BOT-IoT, KDDS99, NSL-KDD datasets in identifying attacks such as Sybil, flooding, and spyware threats. SVM utilizes UNSWNB15, KDDCUP99, NSL-KDD, and NOT-IoT datasets in the detection of man-in-the-middle attacks, DoS, DDoS, and tampering. Also, DL techniques like Deep Neural Networks (DNNs), Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs) are preferred over ML-based approaches while dealing with larger datasets [188; 189].
## 6 Conclusions  
This paper examined the smoke control effectiveness of vertical and horizontal air curtains in three different scenarios. Regardless of the corridor layout, vertical air curtains were deemed more advantageous for ensuring safety.  
The simulation results indicated that with a wind speed of 35 m/s and using vertical air curtains, the soot concentration decreased by 80-99% compared to no air curtains, depending on the case. Horizontal air curtains showed a reduction rate of 65-99% in different scenarios. In most cases, the installation of vertical air curtains proved to be more beneficial than horizontal ones.  
Comparing the hot smoke test with the simulation, the visible smoke control effect was similar when a 10 m/s vertical air curtain was installed and the fire door was open. This indicates that in an actual fire, the installation of vertical air curtains could reduce the ingress of smoke into stairwells from corridors.  
In cases where the stairwell is adjacent to a corridor that is not straight, setting the angle of the air curtain outside of protruding parts to prevent turbulence formation inside the stairwell appears to be advantageous for smoke control. Ventilation conditions may vary depending on the corridor layout and stairwell opening design, and additional experiments may be needed for air curtains with external air supply units, as opposed to integrated ones.  
Based on the results of this study, it is believed that air curtains can partially reduce smoke ingress in stairwells of older buildings or low-rise structures without pressurization systems, thereby ensuring fire safety.  
Conceptualization, K.K. and D.S.; Methodology, K.K. and D.S.; Software, K.K.; Investigation, K.K.; Data curation, K.K.; Writing--original draft, K.K.; Writing--review & editing, K.K. and D.S.; Supervision, D.S.; Project administration, D.S. All authors have read and agreed to the published version of the manuscript. This research received no external funding.  
Not applicable.  
The raw data supporting the conclusions of this article will be made available by the authors on request.  
Figure 19: Photo of the experiment site (**a**) 10 s after opening the fire door without an air curtain, (**b**) 10 s after opening the fire door with an air curtain.  
Conflicts of Interest: Author [PERSON] was employed by the company Korea Fire & Explosion Solutions Corporation. 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.