esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction  
Welding is a major way to produce metal structures such as stiffened plate panels [1]. Thus, the global consumption of welding consumables is enormous, and the market was valued at USD 13.79 billion in 2018, according to market-watch research [2]. There are generally two kinds of welding consumables, categorized by shape: (1) stick, such as stick electrodes, and (2) wire, including solid wires, flux-cored wires, and submerged arc-welding (SAW) wires. Wire-shaped welding consumables such as metal-inert gas (MIG) welding wire are usually wound onto small plastic spools for sale, with final weights of about 5-30 kg [3].  
However, the winding process currently relies on manual operation, as shown in Figure 1, resulting in limited capacity and high cost. Furthermore, the operation requires repetitive heavy work in a noisy workshop, which presents health risks to workers. Besides the repetitive operation of clamping-disk loading and unloading and nut tightening and loosing, there is another major obstacle for fully automatic welding wire winding, which the insertion of the main axle and drive rod on the spindle, as shown in Figure 2a, precisely into the main bore and drive bore of the spool, as shown in Figure 2b. Only after this operation is completed is the spool ready to be driven, rotating together with the spindle. This operation requires high speed, and accurate and robust measurement of the spool's angular position.  
Therefore, this paper proposes a template-matching-based method to measure the angular position of the spool and provide the rotational angle, and presents a mechanical system that can lift the spool coaxial onto the spindle and rotate the spool to match the drive rod. Moreover, a novel feature-point distribution density (FPDD) strategy is proposed to accelerate the matching process and improve matching reliability by pre-locating the searching area. The angular-position-measuring method was validated using a built prototype of the mechanical system.  
The remainder of this paper is organized into the following structure: relevant work for this study is summarized in Section 2; the designed mechanical system is presented in Section 3; the proposed method is described in Section 4; the experimental comparison results are discussed in Section 5; and conclusions are summarized in Section 6.  
Figure 1: Manual operation of welding wire winding. The spool is installed onto the spindle, clamped by the clamping disk, and fastened by a nut. A swing arm is applied to assist the worker to load and unload the clamping disk.  
Figure 2: The spindle structure of a current winding machine (**a**) and the welding wire spool (**b**).
## 5 Experimental Simulation and Analysis
### SLP-MACGT Comparison with Other SLP Schemes
#### 5.3.2 End-to-End Delay  
Figure 9a shows that in terms of latency, SLP-MACGT exhibits significantly lower end-to-end latency compared to SSLP, PP-SLPP, and MRGSLP. While PP-SLPP, SSLP, and MRGSLP experience a notable increase in latency due to the utilization of AUVs, with latency on the order of minutes, the latency magnitude of SLP-MACGT is on the scale of seconds. Specifically, the higher latency in PP-SLPP compared to SSLP is attributed to the time taken for the leading AUV to collect data from all following AUVs, whereas in SSLP, AUVs collect data based on trajectories without significant delays. MRGSLP divides the network into static and dynamic layers, with nodes in the static layer requiring AUV assistance for data transmission.  
Moreover, Figure 9a indicates that latency increases with the growth of the network edge length. In Figure 9b, the fluctuations in PP-SLPP latency stem from variances in pushing positions and random initial positions of AUV groups. The latency of SSLP increases with the rising number of nodes as AUVs collect data from more nodes along fixed trajectories. In SLP-MACGT, as the number of nodes increases, senders can choose the next hop nodes closer to the convergence node, resulting in a gradual decrease in latency as node count rises.
# A Novel Method for Detecting Advanced Persistent Threat Attack Based on Belief Rule Base
## 3 The BRB-Based APT Detection Model
### APT Detection Method Based on BRB
#### 3.2.2 Feature Extraction from IP Packets  
The four features mentioned in the previous section can be extracted from the information obtained from IP packets. The traced path is derived from IP addresses, but IP addresses cannot be used directly as traced paths. It is difficult to construct rules on a host-by-host basis in a large network with many hosts because there will be too many attributes and reference values for BRB, which will lead to an exponential explosion problem. Host address requires information extraction. As mentioned above, the value of the host is important, and it can be represented on the network by an IP address. When there are many hosts of equal value, it is not necessary to determine the location of each host, but to treat them as an area. Converting IP address paths to area paths can solve the exponential explosion problem encountered in setting rules for BRB. Therefore, hosts are divided into different areas by expert knowledge based on their role and value. The IP address paths are then converted into the area paths by replacing the IP address with an area. The area paths are the traced paths. When the wrong sequence of areas appears, it can be considered as an anomaly. The traffic rate, average time interval, and average transferred bytes can be calculated from the information obtained from IP packets. The traffic over a period of time is a sample that contains both APT traffic and normal traffic. The processing flow can be represented as Figure 2.The detailed steps of feature extraction are as follows:  
1. [label=**Step 1**]
2. Tracing anomalous paths by IP address. For example, a path is from A to B to C to D.
3. Calculating the total bytes transferred by each path. The total number of bytes is the sum of the transferred bytes from A to B, B to C, and C to D.
4. Calculating the time interval of every two neighboring nodes in the path and, then, sum up. The time interval is the time interval from A to B and B to C plus the time interval from B to C and C to D.
5. Replacing malicious IP paths with malicious area paths.
6. Fusing the same malicious area paths. Averaging over the transferred bytes and the time interval. Recording the number of fusions per path.
7. Doing **steps 1** to **5** for normal traffic as well.
8. Calculating the rate of paths among all paths using the number of fusions of paths.  
By processing the original data, a dataset containing the four features proposed above is now obtained, which can be used to train the model.
# Hand Gesture Recognition on Edge Devices:
###### Abstract  
Hand gesture recognition (HGR) is a convenient and natural form of human-computer interaction. It is suitable for various applications. Much research has already focused on wearable device-based HGR. By contrast, this paper gives an overview focused on device-free HGR. That means we evaluate HGR systems that do not require the user to wear something like a data glove or hold a device. HGR systems are explored regarding technology, hardware, and algorithms. The interconnectedness of timing and power requirements with hardware, pre-processing algorithm, classification, and technology and how they permit more or less granularity, accuracy, and number of gestures is clearly demonstrated. Sensor modalities evaluated are WIFI, vision, radar, mobile networks, and ultrasound. The pre-processing technologies stereo vision, multiple-input multiple-output (MIMO), spectrogram, phased array, range-doppler-map, range-angle-map, doppler-angle-map, and multilateration are explored. Classification approaches with and without ML are studied. Among those with ML, assessed algorithms range from simple tree structures to transformers. All applications are evaluated taking into account their level of integration. This encompasses determining whether the application presented is suitable for edge integration, their real-time capability, whether continuous learning is implemented, which robustness was achieved, whether ML is applied, and the accuracy level. Our survey aims to provide a thorough understanding of the current state of the art in device-free HGR on edge devices and in general. Finally, on the basis of present-day challenges and opportunities in this field, we outline which further research we suggest for HGR improvement. Our goal is to promote the development of efficient and accurate gesture recognition systems.  
Keywords:hand gesture recognition; edge machine learning; artificial intelligence; algorithms; signal processing; radar; WiFi; 4G; 5G; LTE; ultrasound; lidar; vision; image processing; AI accelerators +
Footnote †: journal: Sensors
# Photocatalytic Inactivation as a Method of Elimination of _E. coli_ from Drinking Water
## 1 Introduction
### The Different Strains of Escherichia coli
#### 1.2.2 The Enterohaemorrhagic O157:H7 Strain  
After the outbreak in 1982, _E. coli_ O157:H7 became the most widely known enterohaemorrhagic _E. coli_ (EHEC) strain [26]. Shiga toxin production, a characteristic feature of the pathogenesis of bloody diarrhea, was reported in Hemorrhagic Colitis outbreak caused by _E. coli_ O157:H7 strain in the United States [26; 28; 30]. The ability to produce Shiga toxins is the common characteristic of all EHEC, and they are often referred to as Shiga toxin-producing _E. coli_ (STEC) [26]. _E. coli_ O157:H7 has been implicated in the death of the elderly, the very young, and the immunocompromised including serious food poisoning leading to product recalls [1]. Its pathogenicity coupled with its ability to survive environmental stress make it a powerful threat to public health efforts. It is resistant to commonly used methods for controlling bacteria such as boiling. The conventional means of isolating other _E. coli_ are not effective in the isolation and identification of enterohemorrhagic _E. coli_ 0157:H7 because it has some biochemical differences from most other _E. coli_ strains [1; 26; 28; 30]. For example,  
* Ninety percent of other strains of _E. coli_ cannot ferment sorbitol but 0157:H7 strain can ferment it [1; 26; 28; 30].
* It does not produce functional \(\beta\)-glucuronidase, whereas most of the other _E. coli_ strains are positive for this test [1; 26; 28; 30].
* Unlike the other 60% non-sorbitol fermenting _E. coli_, the 0157:H7 strains will not ferment rhamn on nutrient agar [1].  
Therefore, special techniques such as DNA probes and polymerase chain reaction (PCR), ELISA procedure utilizing the monoclonal antibody (4 ESC12) are used in the isolation of _E. coli_ 0157:H7 [1].
# Review of Acoustic Sources Alternatives to a Dodecahedron Speaker
## 2 Acoustic Source Alternatives to a Dodecahedron Speaker
### Inverse Horn Design
Applying the proposed inverse filtering has many advantages: it flattens the frequency response, shortens the time response making the signal of the source more adequate for acoustical measurements and improves omnidirectionality. Inverse filtering was also utilized for other inverse horn design implementations [107; 113]. Relating to sound pressure levels, 85 dB in each one-third-octave band between 100 Hz and 5 kHz and 102 dB full band was measured [105]. A little higher sound pressure levels can be found in a commercial implementation [114]. The inverse horn design has lower levels than traditional omnidirectional sources (dodecahedron speakers). However, since signals such as MLS [106; 113] are usually utilized for acoustic measurements with the inverse horn design, synchronous averaging can be applied, thus enhancing the signal-to-noise ratio. In regard to measurements of acoustic parameters, research where the inverse horn design was utilized as an alternative source and results obtained were compared with measurements with a dodecahedron speaker or another source could not be found in the literature. Since the source fulfills ISO 3382-1 requirements then it should provide similar results for the measurement of acoustic parameters compared with dodecahedron speakers. However, the inverse horn design was used as an omnidirectional source according to the ANSI S1.18 standard [115] for the measurement of ground impedance in a study by [PERSON] et al. [106]. In conclusion, the inverse horn design as a sound source meets the ISO 3382-1 criteria since it fulfills the requirements for omnidirectionality and emits acceptable sound pressure levels. Considerations should be taken in order to avoid contamination by background noise in acoustic measurements, especially in the low-frequency range.
# Experimental Analysis of Transformer Core Vibration and Noise under Inter-Harmonic Excitation
## 4 Conclusions  
As important equipment in the power system, the transformer contains the problem of abnormal increase in vibration and noise caused by inter-harmonic excitation, which needs to be studied urgently. In this work, an experimental circuit that can generate arbitrary inter-harmonic excitations is first built according to the experimental requirements. Then, vibration measurement equipment and a noise sound level meter were used to test the vibration and noise of transformer core under conditions of different inter-harmonic frequencies and amplitudes. The following conclusions are drawn through the experimental results:  
1. When the excitation voltage contains inter-harmonics of a single frequency (the inter-harmonic frequency is \(f_{th}\)), the transformer core contains components with frequencies that are integer multiples of the fundamental frequency as well as inter-harmonic components of other frequencies. Inter-harmonic frequencies exist at \(\pm f_{th}\) of even harmonics of the fundamental frequency and \(\pm f_{th}\) of odd harmonics of the fundamental frequency.
2. Inter-harmonics have a serious impact on the vibration and noise of the transformer core (especially the inter-harmonics with a frequency lower than 20 Hz). Vibration and noise increase with the decrease of the inter-harmonic frequency and the increase of the amplitude, and the effect of inter-harmonics is more obvious with the voltage amplitude increase.  
The test platform and experimental conclusions of transformer core vibration and noise characteristics under inter-harmonic excitation in this paper provide effective reference and data support for such experiments.  
Figure 11: Noise level under excitation with different inter-harmonic content; (**a**) With 5 Hz inter-harmonics; (**b**) With 20 Hz inter-harmonics; (**c**) With 40 Hz inter-harmonics.  
**Author Contributions:** Conceptualization, Q.H.; methodology, C.F.; validation, G.Y.; writing--original draft preparation, G.Y. and J.L.; writing--review and editing, G.Y. and H.L.; project administration, Q.H. and X.C. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Scientific and Technological Project of Global Energy Interconnection Research Institute Co., Ltd. (Grant No.525500200050).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# TTH-Net: Two-Stage Transformer-CNN Hybrid Network for Leaf Vein Segmentation
## 3 The Proposed Method
### First Stage: Coarse-Grained Feature Extraction  
To model the long-range dependencies of leaf veins, the Vision Transformer (ViT) [15] is used for more representative features. Different from CNN, ViT expands the receptive field based on the entire leaf image by self-attention module, which results in strong global modeling capability. Thus, in this paper, we take ViT as the encoder to capture coarse-grained vein features.  
Specifically, the ViT encoder consists of self-attention modules, Multi-Layer Perceptron (MLP), and LayerNorm. The input \(\mathrm{X}\in\mathrm{R}^{\mathrm{H}\times\mathrm{W}\times\mathrm{C}}\) (H, W, and C are height, width, and channel dimensions, respectively) is first split into N flattened patches, where \(\mathrm{N}=\mathrm{H}\times\mathrm{W}/\mathrm{P}^{2}\) and \(\mathrm{P}\) is the width/height of each patch. As a result, the original input is reshaped into \(\mathrm{X}_{\mathrm{P}}\in\mathrm{R}^{\mathrm{N}\times\mathrm{P}^{2}\times \mathrm{C}}\). By flattening these patches into one-dimensional vectors and projecting them linearly, we obtain the input \(\mathrm{E}_{\mathrm{v}}\) of ViT. To compensate for the lost positional information during the patching, \(\mathrm{E}_{\mathrm{p}}\) is added into \(\mathrm{E}_{\mathrm{v}}\) and forms a new input z. After the LayerNorm function and linear mapping operation, we obtain the Query (Q), Key (K), and Value (V). Then, we utilize the self-attention module to model the global dependency of the vectors for accuracy improvements, which can be calculated as  
\[Attention(Q,\ K,\ V)=Softmax(\frac{Q\cdot K^{T}}{\sqrt{d}})V \tag{1}\]  
where d represents the dimension of feature vectors. After the residual connection, \(z_{\mathrm{s}}\) is generated. The LayerNorm function and MLP are used to integrate contexts and output \(z_{\mathrm{s}}^{\prime}\), which can be formulated as  
\[z_{\mathrm{s}}^{\prime}=MLP(LN(z_{\mathrm{s}}))+z_{\mathrm{s}} \tag{2}\]  
Finally, by repeating the above process, we obtain the coarse-grained results. To facilitate the recovery of fine-grained features in subsequent steps, we retained the results from the third, sixth, ninth, and twelfth layers and reshaped them into the 2D features. Note that these features have the same resolutions. In addition, we also introduce four additional auxiliary losses to guide ViT in extracting coarse-grained feature representations.
# A Spectrum Management Platform Architecture to Enable a Sharing Economy in 6G
###### Abstract  
We propose a novel vision to trade and allocate wireless spectrum in 6G communication networks inspired by the concept of the sharing economy. We argue that such an approach will help ease the surge in demands for wireless spectrum that will characterise the 6G world. We also introduce HODNET (Heterogeneous on Demand NETwork resource negotiation), an open platform that is able to realise this new spectrum-sharing model. To demonstrate the benefits of spectrum trading and allocation in this new paradigm, we considered the use-case of massive Internet of Things (IoT) on a local scale. We simulated a large IoT deployment and evaluated the spectral efficiency of the system when managed using HODNET compared with a standard 5G deployment. Our experiments show that HODNET can indeed offer better allocation, based on our spectrum sharing model, of spectrum resources compared with standard allocation approaches.  
Beyond 5G; 6G; spectrum sharing; software-defined network; massive IoT +
Footnote †: journal:  
the fixed licence model that has been used for nearly a century. Three spectrum frameworks are commonly discussed regarding 5G [3] and include Citizens Broadband Radio Service (CBRS) approaches, Licensed Shared Access (LSA), and Concurrent Shared Access (CSA), which are discussed in more detail in the next section. The key observation however is that all these models still rely on a major licence holder (an entity or a club of entities) which has primary rights and may allow other parties to use spectrum which the major holder is not using, in an only quasi-dynamic way.  
There are frequency bands where allocation (either administrative or market-based) does not apply. Such bands, commonly known as unlicensed frequency bands, are not owned by any entity and can be used freely by stakeholders for a variety of applications [4]. The most well-known frequency band in this class is 2.4 GHz, which is widely used for Wi-Fi, Bluetooth, and many other communication technologies. Here, the spectrum is shared by protocol design but will eventually lead to the complete depletion of the band [5].  
In this article, we propose a new way of sharing spectrum, which is completely based on the dynamic matching of offer and demand of network resources. It is based on the principles of the sharing economy paradigm. The remainder of this paper is structured as follows. Section 2 provides a detailed analysis of the state of the art on spectrum sharing and our novel contributions. Then, in Section 3, we build the case for a new form of spectrum sharing, based on the principles of the sharing economy, and in Section 4, we propose the system architecture with which this can be achieved. We illustrate the benefits of this approach with a use case revolving around massive IoT deployment in Section 5. Final conclusions and significant aspects to explore further are given in Section 6.
# Use of Bilberry and Blackcurrant Pomace Powders as Functional Ingredients in Cookies
## 2 Materials and Methods  
### Raw Materials  
Wild bilberries (_Vaccinium myrtillus_ L.) and blackcurrants (_Ribes nigrum_ L.) harvested from the hills of Valcea county, Oltenia Region, South-West Romania (44\({}^{\circ}\)49\({}^{\prime}\) N 24\({}^{\circ}\)15\({}^{\prime}\) E), were processed into juice without enzymatic treatment (juice yields of 57.6% and 49.3% for bilberry and blackcurrant, respectively) in a small-scale fruit juice factory located in Vaideeni (Valcea county, Romania). The pomaces (two batches of 3 kg for each berry) obtained as juice by-products were collected, packed in polyethylene bags, transported, and stored at \(-\)18 \({}^{\circ}\)C until use. The bilberry and blackcurrant pomaces were thawed in the air at room temperature (20 \({}^{\circ}\)C) and convectively dried in thin layers at 57 \({}^{\circ}\)C in a dehydrator (Deca +SS Design, Profimatic, Cluj-Napoca, Romania). The dried pomaces were thoroughly ground into powders using an electric coffee grinder (Bosch TSM6A011W, Bosch, Munich, Germany), passed through a 0.3 mm sieve, and kept in polyethylene bags at ambient temperature (20 \({}^{\circ}\)C) until cookies manufacturing.  
The wheat flour type 650 (moisture--13.90%; protein--11.93%; fat--1.42%; and ash--0.65%) used for dough and cookie preparation was produced by the Maripan Cereal S.R.L mills (Tuglui, D0j County, Romania). Vegetable fat for pastry (99.7% fat, containing refined palm and sunflower oils, emulsifier--E471, and antioxidant--E320, E321) was provided by Shchedro LLC (Zaporizhizhia, Ucraina), while the baking powder (Alpina) used in the formulation was purchased from Zeelandia S.R.L. (Iasi, Romania). Salt (sodium chloride) and granulated sugar were procured from the local market.