esa-sceva/satcom-chunk-collection huggingface dataset:
_Article_  
Highly Efficient SCA-Resistant Binary Field  
Multiplication on 8-Bit AVR Microcontrollers  
[PERSON] 1,*\({}^{\star}\)\({}^{\copyright}\) and [PERSON] 2  
1 Department of Information Security, Cryptology, and Mathematics, Kookmin University, Seoul 02707, Korea  
2 Graduate School of Information Security and Institute of Cyber Security & Privacy (ICSP), Korea University, Seoul 02841, Korea; [EMAIL_ADDRESS]  
* Correspondence: [EMAIL_ADDRESS]  
Received: 25 March 2020; Accepted: 16 April 2020; Published: 19 April 2020  
**Abstract:** Binary field (\(BF\)) multiplication is a basic and important operation for widely used crypto algorithms such as the GHASH function of GCM (Galois/Counter Mode) mode and NIST-compliant binary Elliptic Curve Cryptosystems (ECCs). Recently, [PERSON] et al. proposed a novel SCA-resistant binary field multiplication method in the context of GHASH optimization in AES GCM mode on 8-bit AVR microcontrollers (MCUs). They proposed a concept of Dummy XOR operation with a kind of garbage registers and a concept of instruction level atomicity (\(ILA\)) for resistance against Timing Analysis (TA) and Simple Power Analysis (SPA) and used a Karatsuba Block-Comb multiplication approach for efficiency. Even though their method achieved a large performance improvement compared with previous works, it still has room for improvement on the 8-bit AVR platform. In this paper, we propose a more improved binary field multiplication method on 8-bit AVR MCUs. Our method basically adopts a Dummy XOR technique using a set of garbage registers for TA and SPA security; however, we save the number of used garbage registers from eight to one by using the fact that the number of used garbage registers does not affect TA and SPA security. In addition, we apply a multiplier encoding approach so as to decrease the number of required registers when accessing the multiplier, which enables the use of extended block size in the Karatsuba Block-Comb multiplication technique. Actually, the proposed technique extends the block size from four to eight and the proposed binary field multiplication method can compute a 128-bit \(BF\) multiplication with only 3816 clock cycles (\(cc\)) (resp. 3490 \(cc\)) with (resp. without) the multiplier encoding process, which is almost a 32.8% (resp. 38.5%) improvement compared with 5675 \(cc\) of the best previous work. We apply the proposed technique to the GHASH function of the GCM mode with several additional optimization techniques. The proposed GHASH implementation provides improved performance by over 42% compared with the previous best result. The concept of the proposed \(BF\) method can be extended to other MCUs, including 16-bit MSP430 MCUs and 32-bit ARM MCUs.  
**Keywords:** authenticated encryption; binary field arithmetic; GHASH function; Galois/Counter Mode of Operation; Simple Power Analysis; Timing Analysis; Binary Elliptic Curve Cryptosystem; 8-bit AVR; ATmega128
## 3 Methodology and Proposed Model
### Data Pre-Processing  
Pre-processing is an essential stage in the data pipeline, involving various techniques and operations to transform raw data into a format suitable for analysis or machine learning model use. This subsection outlines the pre-processing steps, including data cleaning, data encoding, data augmentation, feature engineering, and data normalization, that will be applied to enhance the accuracy of employee attrition prediction.
# Process Mining IPTV Customer Eye Gaze Movement Using Discrete-Time Markov Chains +
## 3 Methodology
### Fitting into a DTMC Model
#### 3.4.4 Summary of Data Pipeline  
The pipeline of data throughout our study from collection to analysis is presented in Figure 12 below:  
We can see that the raw data originated from the eye tracker, was initially stored by Tobii Studio, and then exported via.csv files, thereby being transferred to a MongoDB database (Step 1). Afterwards, the data was cleansed using a Java program (Step 2) and then passed into a MySQL database (Step 3). Before records could be saved into the MySQL database, the Java program converted gaze point coordinates to block labels. In Step 4, a Java program accessed the MySQL database and calculated the properties of  
Figure 12: Data pipeline throughout our study [16].  
the DTMC model (i.e., the transition matrix and the initial state distribution). Lastly, in Step 5, the Java program created some.csv files containing DTMC metrics for MATLAB (\"**content purchase\"** scenario) or R Studio (\"**content viewing\"** scenario) to employ. Then, in MATLAB, functions such as \"dtmc\" and \"graphplot\" were implemented, while in R Studio, we used functions mostly from the \"markovchain\" package, subsequently to create and observe DTMC models.
# ZONE-Based Multi-Access Edge Computing Scheme for User Device Mobility Management
## 6 Conclusions  
This paper makes the following points. First, it shows that the MEC brings computing capacity to the edge of the mobile network, which enables the mobile user to run applications that require ultra-low delay service to meet strict requirements. However, when mobile users move to other access MECC in MEC environment, there are problems that the existing MEC environment does not consider, such as efficient utilization of computing resources and efficient task migration. To solve this problem, we propose a mobile user mobility support scheme that manages access MECS as the concept of Zone in this paper. In other words, the proposed scheme can efficiently support the movement of mobile users by using the information generated by the EMO and ZMO that manages the access MECS. Therefore, it is possible to provide continuous service delivery and efficient task migration even when mobile users frequently moves. We also show that the proposed scheme is an improvement over the existing MEC architecture through performance evaluation in the simulation environment, resulting in faster service delivery and lower task migration failure rates. In future works, we will improve the proposed scheme by implementing artificial intelligence (AI) features to enable continuous service delivery and efficient service discovery even when mobile users are moving frequently.  
[PERSON]. ([PERSON]) and [PERSON] ([PERSON]) conceived and designed the experiments; [PERSON]. ([PERSON]) performed the experiments; [PERSON]. ([PERSON]), [PERSON] ([PERSON]) and [PERSON] analyzed the data; [PERSON]. ([PERSON]) contributed reagents/materials/analysis tools; and [PERSON] ([PERSON]), [PERSON] and [PERSON]. ([PERSON]) wrote the paper.  
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. 2016R1D1A1B03931628) and (No. 2017R1D1A1B03034215).  
The authors declare no conflict of interest.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} MEC & Multi-Access Edge Computing \\ MECS & Multi-Access Edge Computing Server \\ IoT & Internet of Things \\ ML & Machine Learning \\ AR & Augmented Reality \\ GCP & Google Cloud Platform \\ EC2 & Amazon Elastic Compute Cloud \\ UHD & Ultra-High Definition \\ ETSI & The European Telecommunications Standard Institute \\ RAN & Radio Access Network \\ vMSG & virtualized Mobility Support Gateway \\ QoS & Quality of Service \\ MPTCP & MultiPath TCP \\ EMO & Edge Management Orchestra \\ ZMO & Zone Management Orchestra \\ AMR & Access MECS Registry \\ UUID & Universally Unique Identifier \\ SHA & Secure Hash Algorithm \\ EML & Edge Management List \\ AMS & Access MECS Status \\ ZU & Zone Update \\ ZML & Zone Management List \\ \end{tabular}
## 11 Further Research Directions and Future Considerations
### Photonic Integrated Circuit Exploitation  
The conventional Co-Rxs that are based on 90\({}^{\circ}\) optical hybrids usually present an issue regarding the distortion in the received \(IQ\) signals. This can be attributed to hardware impairments during the fabrication process. For instance, the amplitude imbalances may be owed either to phase-diversity networks, coupling mismatches, or PD responsivities. The imbalances can result in adjacent channel interference, constellation distortion, and common-mode-rejection-ratio (CMRR) degradation. Although it is possible to employ complex DSP algorithms for the partial mitigation of constellation distortion, the CMRR correction and nonideal filter effects reduction are very challenging with the conventional DSP-based algorithms. To address the associated challenges, PIC receivers in which 120\({}^{\circ}\) hybrids are leveraged could be potential candidates. This is owed to the related better bandwidth performance and chip size reduction with merely three single-ended detectors. Through a linear calibration process, the hardware impairments can be alleviated. This brings about virtually perfect received \(I/Q\) signals and enhanced CMRRs, which implies better performance. Furthermore, the energy consumption can be reduced and the DSP workload can be alleviated compared with relatively complex DSP techniques [173]. Furthermore, apart from its capability to support a dense number of ports, photonic integration can efficiently support component sharing. For instance, a number of integrated WDM lasers can collectively share thermoelectric cooling rather than one for each. This can really help address the challenges of a growing increase in the lane rate [16]. Furthermore, PIC will facilitate integrated transmitter and receiver structures. With the integration, the system cost and form factor will be considerably reduced. Apart from the fact that it will ease signal generation, the integration will also facilitate chromatic dispersion precompensation and WDM multiplexing [35]. Nevertheless, there are some design and technical challenges that are specific to PIC technologies. For instance, concerted efforts are required to address the associated issues regarding the yield, assembly, packaging, circuit modeling, thermal management, process compatibility, RF interface management, ecosystem development, on-chip elements' optimization, and manufacturing [174].
## 3 Results and Discussion
### Characterization of Triple-Cation Perovskite Thin Films
#### 3.1.2 Optical Properties of Mixed-Cation Perovskite Thin Films  
To investigate the optical properties of the fabricated perovskite thin films, UV-Vis absorption spectroscopy and Tauc plot analyses were performed, and the results are shown in Figure 4.  
Figure 4a shows the absorption spectra of pure and Cs-incorporated (Cs = 0.03, 0.05, and 0.10) FAMAPbI\({}_{3}\) thin films. All the films exhibited strong absorption characteristics in the UV-Vis region. With the incorporation of Cs, the absorption of the films increased, with the most significant increase observed at Cs = 0.05. This suggests that Cs incorporation enhanced the crystallization of the films and reduced their defect density, leading to improved light-absorption properties.  
Figure 4b shows the results of the Tauc plot analysis, where (ahv)\({}^{2}\) is plotted against the photon energy (hv). With an increase in the Cs content, the absorption edge shifted, indicating a change in the optical bandgap of the films.  
The pure FAMAPbI\({}_{3}\) thin film (Figure 4b, dotted line) showed a basic bandgap, which increased with the introduction of Cs. The highest bandgap was observed at Cs = 0.05 (solid line), while at Cs = 0.10 (dash-dot line), the bandgap decreased again. These results indicate that the introduction of Cs affected the crystal structure and defect states of the thin films, resulting in changes in their electronic structure.  
The increase in the bandgap can be interpreted as the optimal amount of Cs adjusting the lattice structure, reducing defects, and enhancing crystallinity. However, when the Cs content was increased to 0.10, the bandgap decreased again, likely because of the lattice contraction and increased structural disorder caused by excess Cs [26].  
Although the Cs content in our samples was relatively low (up to 0.10), we acknowledge that the non-monotonic trend in the bandgap values could also arise from local structural inhomogeneities or early-stage phase segregation, as reported in previous stud  
Figure 4: UV-vis absorption and Tauc plot analyses of FAMAPbI\({}_{3}\) with varying Cs contents: (**a**) absorption spectra, (**b**) Tauc plot analysis.  
ies [28]. Further investigations, such as PL mapping or grazing-incidence wide-angle X-ray scattering (GIWAXS), would be required to confirm the phase purity in future works.
# Multidisciplinary Reliability Design Optimization Modeling Based on SysML
###### Abstract  
Model-Based Systems Engineering (MBSE) supports the system-level design of complex products effectively. Currently, system design and optimization for complex products are two distinct processes that must be executed using different software or platforms, involving intricate data conversion processes. Applying multidisciplinary optimization to validate system optimization often necessitates remodeling the optimization objects, which is time-consuming, labor-intensive, and highly error-prone. A critical activity in systems engineering is identifying the optimal design solution for the entire system. Multidisciplinary Design Optimization (MDO) and reliability analysis are essential methods for achieving this. This paper proposes a SysML-based multidisciplinary reliability design optimization modeling method. First, by analyzing the definitions and mathematical models of multidisciplinary reliability design optimization, the SysML extension mechanism is employed to represent the optimization model based on SysML. Next, model transformation techniques are used to convert the SysML optimization model generated in the first stage into an XML description model readable by optimization solvers. Finally, the proposed method's effectiveness is validated through an engineering case study of an in-vehicle environmental control integration system. The results demonstrate that this method fully utilizes SysML to express MDO problems, enhancing the efficiency of design optimization for complex systems. Engineers and system designers working on complex, multidisciplinary projects can particularly benefit from these advancements, as they simplify the integration of design and optimization processes, facilitating more reliable and efficient product development.  
model-based systems engineering; SysML; multidisciplinary design optimization; reliability analysis +
Footnote †: journal: Applied Sciences  
1
Footnote 1: [[https://doi.org/10.3390/app14177558](https://doi.org/10.3390/app14177558)]([https://doi.org/10.3390/app14177558](https://doi.org/10.3390/app14177558))
## 2 Methods  
Three key factors are considered for PSSs detection. First, the detector should achieve multi-scale object detection without additional prior anchors. Second, the detector should mine the critical information of targets and learn the powerful feature representation. Third, the detector needs to balance the background and foreground samples.  
To alleviate these issues, we propose a feature enhanced anchor-free network for PSSs detection in RSIs. The network architecture mainly consists of three parts, backbone, enhanced feature layers, and detection head. An enhanced feature module (EFM) is designed for improving the discrimination ability of the model. A context-aware strategy is introduced for suppressing more negative samples. Additionally, focal loss is used to balance the positive and negative samples and CIoU loss is used to further optimize model training.
## 3 Experimental Setup
### Justification of Firewall  
Placing a firewall in the investigation network allows the control to detect the app behavior effectively. Firewall rules are used to confirm the default app behavior. Furthermore, restrictions can be applied, and ulterior app behaviors can be brought to light. Default and alternate traffic patterns can assist the forensics examiners in solving the cases involving Signal or any other app. Moreover, it also helps in observing the client-server connectivity design pattern such as TCP/UDP ports and server ranges, etc. In this scenario, firewall configuration requires defining rules according to network requirements for both WAN and LAN. By default, both inbound and outbound traffic are blocked through the firewall. The LAN rules are defined to configure access to internet resources. As a standard practice, there are no rules defined for WAN NIC which means all inbound traffic are blocked unless configured. If there is any web server in a network, a WAN rule can be defined to access that server.  
The _packet capture_ option in the firewall interface is used to capture the live traffic of the target device as shown in Figure 3. Explicit capturing of smartphone traffic of the Signal app through a firewall or any other device in the network is possible with the help of IP addresses as shown in Figure 4. This helps to reduce the reliance on port mirroring deployed in the setup explained in the paper [18]. The captured live network traffic is saved from LAN/WAN as trace files which are then analyzed using Wireshark.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Device/Tool** & **Purpose** & **Company** & **Software/OS** \\ \hline Firewall & Capturing and monitoring & & & 2.4.4-RELEASE-p3 and FreeBSD version \\ Firewall & network packets in the traffic. & & & 11.2-RELEASE-p3 \\ Firewall rules & & & & \\ \hline CISCO switch & WAN connection & CISCO & SG300-52 port Gigabit Cisco Layer-3) \\ \hline Wireless Access Point (WAP) & Used as bridge & PTCL & PTCL, DSL-2750U \\ \hline Smartphone & To perform user activities on & & & Android OS version 9 \\ Signal app & & & & \\ \hline Desktop Computer & To deploy firewall and & & & Windows 10, 64- bit Operating system \\  & Wireshark & Dell & that has an x64-based processor, 4 GB \\  & & & RAM, Intel (R) Core (TM) i5-3470 CPU \\  & & & & @3.20 GHz. \\ \hline Wireshark & To read the network trace & & Version 3.0.6 \\ \hline Signal application & To perform major activities & Signal Foundation & Version 4.58.5 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Devices and tools specifications for experimental setup.
# Attention-Guided Wireless Channel Modeling and Generating
## 3 Modeling and Generating
### Se-Gan  
This study incorporates the channel attention module (Squeeze-and-Excitation layer, SEL) into the generator of WGAN-GP, our model adaptively recalibrates the importance of each feature channel, focusing on features critical for accurate channel modeling. This method not only strengthens the model's ability to capture channel characteristics but also elevates the quality of generated channel samples. Moreover, the introduction of the attention mechanism fosters improved training stability and efficiency, allowing the model to adeptly adjust to complex and dynamic wireless environments. Overall, this innovative combination of attention mechanisms with WGAN-GP provides a fresh perspective and an effective tool for wireless channel modeling, showcasing substantial improvements and benefits.  
The channel attention module SEL is an advanced channel attention mechanism that plays a crucial role in deep neural networks by adaptively assigning varying levels of importance to different feature channels. This module is designed to enhance the representation capabilities of the network by recalibrating the channel-wise feature responses. The underlying idea is that not all feature channels contribute equally to the task at hand, and some channels may contain more valuable or task-specific information. Therefore, it is essential to focus more on these critical channels while suppressing less informative ones. It is designed to assign varying degrees of importance to different feature channels based on their contributions to the model's outputs. Some channels may contain more valuable information for the specific task. By introducing a mechanism that adaptively adjusts the importance of each channel, the model focuses on the most critical feature channels, thereby enhancing overall performance. Figure 3 illustrates the structure of SEL, which consists of three main parts: global spatial information compression, feature channel recalibration, and feature reweighting.
# An Action Classification Method for Forklift Monitoring in Industry 4.0 Scenarios
## 4 Experimental Analysis
### Discussion  
A discussion on possible alternatives to this algorithm must be conducted. As reported in [25], it is possible to measure the radial speed \(v_{r}\) of a tag with respect to the reader antenna through the acquisition of the Doppler frequency shift. Indeed, the tag radial speed measurements in the asymmetrical antenna deployment can be profitably used for the forklift action classification similarly to (9). To obtain reliable Doppler frequency shift data, the reader manufacturer suggests to configure the Impinj Speedway R420 reader to low reading-rate modes [43]. In such way, the duration of the RFID signal packets is longer; therefore, the Doppler frequency shift is easier to be measured. However, such a condition does not fit with our need to have fast readings to ensure both the forklift and the goods detection and to satisfy the Nyquist-Shannon Sampling Theorem. Therefore, during the tests, we had to configure the reader to a fast reading-rate mode, so the Doppler frequency shift measurements were affected by severe detrimental noise. Consequently, the here proposed signal processing Equation (9) resulted in a more robust, reliable and accurate action classification method. Additionally, the fast-rate reader configuration allows minimizing the number of cases where the Sampling Theorem is not met and phase unwrapping fails. Another aspect that must be considered is the Doppler shift \(\Delta f=2 fv_{r}/c\), when the forklift travels at high speed, e.g., \(v=3\) m/s, \(\Delta f<17.31\) Hz. Given that the bandwidth for a single RFID channel in the ETSI European lower band is 200 kHz [44], such \(\Delta f\) can be considered negligible and difficult to measure. Finally, the proposed method does not require any preliminary system calibrations, and can be implemented with COTS devices.