esa-sceva/satcom-chunk-collection huggingface dataset:
# Cyclotomic Trace Codes
## 1 Introduction  
In Reference [1], [PERSON] introduced a generic construction of linear codes using a defining set \(D\) and the trace function. Many classes of known codes can be produced by choosing an appropriate defining set [2; 3; 4; 5; 6]. Some of these codes support combinatorial 2-designs [7; 8].  
In Reference [7], [PERSON] considered linear codes obtained by choosing the defining set \(D\) to be the set of all nonzero squares in \(GF(p^{m})\), where \(p\) is an odd prime.  
In this paper, we generalize [PERSON]'s construction from Reference [7], by choosing the defining set \(D\) to be the set of all \(s\)th powers of nonzero elements in a field \(GF(p^{m})\), where \(p\geq 2\) can be any prime, and \(s\geq 2\). Our construction generalizes and expands [PERSON]'s construction [7] in two ways--we use as defining sets arbitrary powers of nonzero elements of \(GF(q)\), where \(q\) can be odd or even, while [PERSON] uses only the set of nonzero squares (\(s=2\)) and \(q\) is odd. If \(s\) is relatively prime to \(p^{m}-1\), the resulting code is a one-weight code, hence equivalent to a sequence of dual Hamming codes (cf. References [9; 10; 11]), while when \(s\) is not relatively prime to \(p^{m}-1\), some interesting two-weight codes are obtained that give rise to strongly regular graphs, block designs and quantum codes. Block designs are constructed as support designs for a given nonzero weight (for other recent research on block designs arising from codes, see Reference [12]). The resulting strongly regular graphs have as vertices the codewords, where two codewords are adjacent if they are at minimum Hamming distance from each other [13; 14].  
Besides codes over fields of odd order \(q\), in this paper we also construct linear codes over finite fields of even order.  
In particular, we obtain projective codes over \(GF(4)\) that give rise to optimal or near optimal quantum codes over \(GF(4)\).  
The paper is organized as follows. Section 2 provides the necessary definitions and notation used in the paper. In Section 3, a construction of linear codes with a defining set being the set of all nonzero \(s\)th powers in a field \(GF(p^{m})\) is outlined and the newly found two-weight codes and corresponding strongly regular graphs are presented. In Section 4, we describe support designs and generalized block graphs obtained from the resulting codes.  
The codes have been constructed and examined using Magma [15].
# The Holistic Perspective of the INCISIVE Project--Artificial Intelligence in Screening Mammography
## 4 Results to the Existing Data Repository
### INCISIVE Retrospective Data
\begin{tabular}{c c c c c} \hline \hline
**Manufacturer** & **Bits** **Allocated** & **Bits** **Stored** & **Image Size** & **Service–Object Pair Class** \\ \hline CARESTREAM & 16 & 12 & 6000 \(\times\) 4735 & Computed Radiography \\ Rochester, NY, USA & 16 & 12 & 6000 \(\times\) 4735 & Image Storage \\ \hline FUJIFILM corporation & & & & Breast Tomosynthesis Image \\ Midtown West, & & & & Storage, Computed Radiography \\ Tokyo Midtown & 16 & 12, 14 & 5928 \(\times\) 4728, 2370 \(\times\) 1770, & Image Storage, Digital \\ Akasaka, Minato, & & & 4740 \(\times\) 3540, 2964 \(\times\) 2364 & Mammography X-ray Image \\ Tokyo, Japan & & & & Storage—For Presentation \\ \hline HOLOG Inc. & & & & Secondary Capture Image \\ Marlboough, MA, USA & 16 & 10,12 & 2457 \(\times\) 1892, 425 \(\times\) 268, 4096 \(\times\) 3328, & Storage, Breast Tomosynthesis \\  & & & 2457 \(\times\) 1996, 3328 \(\times\) 2560, & Image Storage, Digital \\  & & & 2457 \(\times\) 1890 & Mammography X-ray Image \\  & & & & Storage—For Presentation \\ \hline  & & & & \\  & & & & \\  & & & & \\  & & & & \\ \hline IMS S.R.L. & 16 & 14 & 3584 \(\times\) 2784, 3584 \(\times\) 2736, 3584 \(\times\) 2720, & Digital Mammography X-ray \\  & & & 3584 \(\times\) 2704, 3580 \(\times\) 2812, 3584 \(\times\) 2768, & Image Storage—For Presentation \\  & & & & \\  & & & & \\ \hline LORAD, Hologic company & & & & Digital Mammography X-ray \\ Bedford, MA, USA & 16 & 16 & 512 \(\times\) 512, 1024 \(\times\) 1024 & Image Storage—For Presentation \\ \hline PHILIPS digital & & & & \\ mammography Sweden, AB & 16 & 16 & 5355 \(\times\) 4915 & Digital Mammography X-ray \\ Solna, Stockholms & & & & Image Storage—For Presentation \\ Lan, Sweden & & & & \\ \hline SIEMENS & & & & \\ Munich, Germany & 16 & 12 & 1882 \(\times\) 1325, 3164 \(\times\) 2364, & Secondary Capture Image \\  & & & & \\  & & & 3241 \(\times\) 2203, 2577 \(\times\) 1006, & Storage, Digital Mammography \\  & & & & \\  & & & 3518 \(\times\) 2800 & For Presentation \\ \hline  & & & & \\  & & & & \\ \hline  & & & & \\ \end{tabular} 
\begin{tabular}{c c} \hline \hline  & & & & & Secondary
## 1 Introduction
[PERSON] (2012, [17]) calculated the side wall deformation and structural internal force of a single-story frame of Zhijing line subway in Beijing with different geological conditions and cover depths. In order to understand the distribution of internal force of the underground shield tunnel under earthquake motions, [PERSON] (2013, [18]) investigated the seismic response of underground tunnels in different site types using a quasi-static method and indicated that such a method was more suitable to underground tunnels in soft foundation. [PERSON] (2013, [19]) proposed a nonlinear static analysis of a rectangular tunnel by using several different simplified numerical methods, and the qualitative relationship between seismic dynamic strength and structure geometry, overburden thickness and soil stiffness were obtained. [PERSON] (2014, [20]) put forward a Pushover analysis method with good accuracy and reliability, which applied to substructure seismic analysis and design. [PERSON] (2014, [21]) studied the influence of foundation liquefaction on the substructure and conducted an experimental study and numerical analysis on the seismic response of a circular subsurface structure using a modified simple calculating method. [PERSON] (2014, [22]) performed a numerical analysis on an arched tunnel using finite element software and found that some given parameters such as the sectional area of arch, and the thickness of surrounding rock and soil characteristic, had a significant influence on the tunnel seismic response. From the above research, it is known that underground structure types become more complicated and there are few studies on the seismic performance of underground substations involving the interaction of soil-structure-equipment. In past studies, such interaction in underground substations was usually ignored, and the seismic response caused by characteristics of electrical equipment and soil were neglected. For these reasons, some positive research is proposed in this paper. A three-dimensional finite element model of an underground substation is established to conduct dynamic numerical simulation analysis. By changing some parameters such as ground motions, properties of surrounding soils, electrical equipment and structure depth, the dynamic results of acceleration amplification coefficients, displacements, stresses and internal forces under different earthquake motions are obtained and analyzed.
## 1 Introduction
Nevertheless, the choice of prediction horizon can significantly affect the control performance. Hence, this work will consider an alternative optimization-based approach widely used in autonomous vehicles: Control Lyapunov Function-Control Barrier Function-Quadratic Programming (CLF-CBF-QP). Lyapunov functions are broadly utilized to demonstrate the equilibrium points' stability in terms of Lyapunov stability, asymptotic stability, or exponential stability [6]. In light of the milestone work of [PERSON] [32] and [PERSON] [33], control Lyapunov functions (CLFs) have emerged as paramount to the control design of nonlinear systems. Barrier functions are prevalent in the control literature owing to their connection with Lyapunov-type functions and capacity to ensure safety [34; 35]. Similar to CLFs, barrier functions were also extended to Control Barrier Functions (CBFs), first presented by [PERSON] et al. [36]. CLF-CBF-QP provides Lyapunov-type conditions for the considered problem to ensure safety. It integrates barrier functions with the control Lyapunov function and harnesses the fast real-time capabilities of quadratic programs [37]. CLF-CBF-QP is an excellent candidate for active suspension control, as it incorporates the Lyapunov function to enhance performance with the barrier function dedicated to guaranteeing safety constraints, more precisely, suspension stroke limits. Limiting suspension travel enables the suspension to absorb severe shocks due to road disturbance without bottoming out or becoming excessively stiff, which is critical for human comfort, vehicle control, and safety. This work considers a quarter-car model featuring a suspension spring with cubic nonlinearity. It formulates the safety-critical CLF-CBF-QP controller for the nonlinear quarter-car model. Our controller design involves two crucial formulations: a Lyapunov function to ensure system stability and performance enhancement, and a barrier function to enforce limits on suspension stroke. Restricting suspension stroke in suspension systems enhances the durability of suspension components, provides steady handling, and provides vital protection for the vehicle and its occupants during ordinary driving and challenging maneuvers.
## 9 Routing in CRSNs
### CRSN Routing Modules
#### 9.1.2.1.1 Full Spectrum Awareness  
For the full spectrum scheme, knowledge of the spectrum availability and channel characteristics is already available and properly documented in specialized servers. Thus, SUs only need to have access to the servers that host the database and can then make communication schedules based on the information. The idea of having a centrally maintained spectrum database that will indicate channel availabilities in the spectrum below 900 MHz and at approximately 3 GHz over time and space is being promoted by the FCC [51]. In this light, [52, 53] proposed measurement-based sensing and modeling techniques for categorizing the channel availability to ease the process of sensing. For resource-constrained nodes, this scheme will be most favorable for enhancing route setup because it solves the problem of trying to synchronize the quiet periods of nodes for spectrum sensing. This approach also gives nodes more time for data transmission because it is known that quiet periods actually reduce node transmission periods. In the long run, this scheme makes route scheduling very effective and can effectively manage mobile nodes.
###### Abstract  
3D modelling of indoor environment is essential in smart city applications such as building information modelling (BIM), spatial location application, energy consumption estimation, and signal simulation, etc. Fast and stable reconstruction of 3D models from point clouds has already attracted considerable research interest. However, in the complex indoor environment, automated reconstruction of detailed 3D models still remains a serious challenge. To address these issues, this paper presents a novel method that couples linear structures with three-dimensional geometric surfaces to automatically reconstruct 3D models using point cloud data from mobile laser scanning. In our proposed approach, a fully automatic room segmentation is performed on the unstructured point clouds via multi-label graph cuts with semantic constraints, which can overcome the over-segmentation in the long corridor. Then, the horizontal slices of point clouds with individual room are projected onto the plane to form a binary image, which is followed by line extraction and regularization to generate floorplan lines. The 3D structured models are reconstructed by multi-label graph cuts, which is designed to combine segmented room, line and surface elements as semantic constraints. Finally, this paper proposed a novel application that 5G signal simulation based on the output structural model to aim at determining the optimal location of 5G small base station in a large-scale indoor scene for the future. Four datasets collected using handheld and backpack laser scanning systems in different locations were used to evaluate the proposed method. The results indicate our proposed methodology provides an accurate and efficient reconstruction of detailed structured models from complex indoor scenes.  
3D reconstruction; indoor modelling; mobile laser scanning; point clouds; 5G signal simulation +
Footnote †: journal:  
Article
## 4 Discussion  
### Methodology  
The methodology used to monitor the thermal cycles was found to be reliable and accurate. The combination of harpooned and inserted K-type thermocouples showed very low dispersion in the measurements, and more than 90% of thermocouples survived. To achieve these results, it was necessary to refine and optimize the methodology by comparing the performance of different thermocouple types (K, N, and C), by checking the influence of insulation material (Inconel(r) vs. glass-fiber) and by exploring different insertion and fitting techniques for the thermocouples [21; 22]. As a result of that preliminary study, the methodology used in this work proved to be suitable and very convenient to study not only super-duplex multi-pass welds, but any kind of multi-pass-welded alloy in which the formation of deleterious phases could be a concern.  
The experimental approach of shortening in length the weld passes in the joint configuration was found to be very useful to follow the evolution of the microstructure in the weld passes. This technique made it possible to obtain one coupon containing the as-deposited pass and the previous ones. Therefore, the microstructure of each single weld pass, in the as-deposited condition could be compared after each one of the reheats experienced.
## 6 Implications
### Multifaceted Causes of Energy Inefficiency  
This review has identified eleven critical factors contributing to energy inefficiency in IoT networks: offloading, scheduling, latency, changing topology, load balancing, node deployment, resource management, congestion, clustering, routing, and limited bandwidth. Each of these factors has a distinct role in influencing the overall energy consumption of IoT systems. By understanding these underlying causes, researchers and practitioners can develop targeted strategies to reduce energy usage and enhance IoT network efficiency.  
The findings underscore the importance of a holistic approach to energy optimisation:  
* Offloading strategies are essential for balancing workload across devices and cloud/fog resources, ensuring tasks are processed in the most energy-efficient manner possible.
* Advanced scheduling mechanisms can streamline operations by prioritising tasks based on urgency and resource availability, thereby reducing processing time and minimising unnecessary energy expenditure.
* Minimising latency is vital to maintaining system responsiveness, particularly for applications with real-time requirements. By reducing latency, IoT systems can operate more efficiently, as less energy is spent on retransmitting data.
* Stable network topologies help reduce power wastage, as devices avoid frequent reconnections and reconfigurations.
* Load balancing ensures a fair distribution of workloads, which prevents any single device or node from becoming overburdened and consuming excess energy.
* Optimal node deployment minimises data transmission distances and enhances communication efficiency, directly impacting energy use.  
Additional factors such as resource management, congestion control, and clustering techniques have been shown to significantly impact energy performance by optimising data flow and reducing transmission redundancies. Moreover, optimised routing protocols can lower energy consumption by identifying the shortest, least congested data paths, while effective bandwidth management prevents bottlenecks and enhances system throughput.
# Train Wheel Condition Monitoring via Cepstral Analysis of Axle Box Accelerations
## 5 Discussion  
### Wheel Condition Monitoring with ABA Sensors  
Wheel monitoring with train-borne sensors means that each wagon needs to be equipped with sensors. In contrast, wayside measurement systems are able to measure conditions of all wheelsets of each passing train with one measurement system. However, on-board systems provide a quasi-continuous monitoring of the wagon, while wayside systems only provide data in certain time intervals, when the train passes. Another advantage of train-borne measurement systems is that they can be used to monitor the track as well, which could justify the high number of sensors. Using broad-band accelerometers below the suspension, in contrast to sensors installed at the bogie or car body, allows to monitor the wheel diameter with very high resolution, which is beneficial for wheel-wear trend analysis. A comprehensive cost-benefit study of available wheel monitoring systems for condition-based and predictive maintenance was not part of this work but should be dealt with in future studies.
## 2 Principles of Underwater Communication
### Communication Mediums in Water
#### 2.1.2 Underwater Electromagnetic Communication (UEC)  
Underwater Electromagnetic Communication utilizes electromagnetic waves that have a limited transmission range due to strong absorption and scattering effects in seawater. Salinity, temperature, pressure, distance, environmental factors, and frequency affect the effectiveness of UEC [17]. High frequencies in seawater experience severe attenuation due to the conductive nature of seawater. In order to enhance range, lower frequencies (30 kHz to 300 kHz) are frequently employed. However, UEC has disadvantages such as high latency, lower data rates, and high attenuation [17].  
In contrast to UAC which benefits from long-distance propagation, UEC requires large antennas to achieve long-distance communication (typically less than 10 m) using RF signals [18].  
Sewater conductivity significantly affects the performance of UEC [17]. To overcome restrictions in electromagnetic communication, magnetic induction (MI) communication can be employed. A time-varying signal is applied to the transmitter coil, and it generates a magnetic field. When the receiver coil comes into the vicinity of the generated magnetic field, both coils are coupled. MI-based communication has a low transmission delay. In contrast to RF and acoustic communication, MI-based communication has no multipath and Doppler effect. The transmission data rate of MI is moderate and typical in Mbps. Also, it provides a stealth operation since there is no audible or visible communication. Therefore, MI-based communication has no impact on marine life [18].  
Compared to RF transceivers, MI transceivers are low-cost. However, there are a few disadvantages of MI-based communication. These systems are orientation-sensitive. Misalignment of transmitter and receiver coils leads to signal distortions. In nature, a transmitter coil is directional and should be perfectly aligned with the receiver coil. Apart from that, seawater conductivity significantly affects MI communication. The range of MI communication depends on the strength of the magnetic field. The range can be increased by increasing the magnetic moment, better coil design, and relaying [18].
# Method for Viewing Real-World Scenes while Recording Video
###### Abstract  
Because smartphones support various functions, they are carried by users everywhere. Whenever a user believes that a moment is interesting, important, or meaningful to them, they can record a video to preserve such memories. The main problem with video recording an important moment is the fact that the user needs to look at the scene through the mobile phone screen rather than seeing the actual real-world event. This occurs owing to uncertainty the user might feel when recording the video. For example, the user might not be sure if the recording is of high-quality and  
Through a focus group discussion (FGD), we investigated the reasons why people feel compelled to concentrate on the mobile phone screen when recording a video. The FGD results indicate that there are several reasons why people focus on the scenes displayed on the mobile phone screen rather than the actual event itself. First, users are concerned regarding whether the target object will be properly recorded. Second, the users cannot be sure whether the video recording contains what they are seeing in real life. If users do not see the mobile phone screen while recording a video, the result of recording sometimes cannot involve the exact scenes the user wants and the quality of recording cannot meet the user's standard. Third, they cannot be sure if the video recording is going well. Focusing on recording the video results in a reduced level of emotion because the user cannot focus on the actual event, and there has been a lack of studies dealing with this issue.  
The technical and practical problems discussed here emerged from the experience of developing and deploying video recording capabilities as a part of research conducted through Samsung's Camera Improvement Project. In this study, we propose new camera functions that support object tracking and head movement recognition. This helps record target objects while tracking them and can record scenes based on the user's head movements.  
Our aim is to help the camera user focus on the real-life event instead of viewing it through the screen. In the aspect of user experience, this will create a better emotional feeling for the user during the video recording. Thus, we proposed a new method to see the real-world scenes while a video recording, which is our main contribution. In addition, we contributed that we measured emotional responses after video recording to verify the effectiveness of the proposed method in the aspect of user experience. In the following sections of this paper, we describe a method proposed to solve the above-mentioned problems. We then evaluate the new system to prove the effectiveness of the proposed application. Although the proposed approach improves the user's positive emotion by allowing the real-world event to be viewed directly while recording a video, further improvements of the application are required.
## 4 Discussion
### Uncertainties, Errors, and Accuracies  
Note that our evaluation of MODIS GPP is based on the assumption that the GPP values measured by the EC flux tower are the ground truth. However, many uncertainties exist in the tower-based GPP measurements [53]. The tower GPP data used in this paper were calculated as the difference between the net ecosystem exchange (NEE) and ecosystem respiration (R\({}_{\text{eco}}\)). The precise estimation of R\({}_{\text{eco}}\) is difficult and can lead to systematic and random errors in estimating GPP. Furthermore, uncertainties also arise due to scale mismatches between the tower flux footprints and MODIS pixels. In addition, the MODIS GPP algorithm itself is also a potential error source in GPP estimation. Recently, many studies have examined the structural errors of the MODIS GPP algorithm [54; 55; 56]. For example, [PERSON] _et al._ (2012) [57] compared the MODIS GPP product with estimates from a two-leaf process-based model. Their results showed that the MODIS GPP algorithm cannot properly treat the contribution of shaded/sunlit leaves to the calculation of the total GPP.  
We should also notice that the number of observations in the regression analysis could affect our estimation results. The seasonal and annual GPP reduced a lot the number of observations in relation to the eight-day data. This could be one reason why the eight-day data gave, in general terms, more accurate estimations.