esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Conclusions  
Impulse-based time hopping ultra-wide band radios are particularly suitable for underlying low-cost low-power consumption communications and positioning, over a huge frequency band where, possibly, other legacy narrow band and broadband wireless systems and electronic devices are active. Both the interferences coming from the narrow band users and the interferences coming from ultra-wide band users should be considered. The FCC's frequency spectral and power spectral density regulations have set restricted conditions that limit the interferences from ultra-wide band radiators to other pre-existing wireless communication systems and electronic devices; however, the issue for in-band strong narrow band interferences suppression in ultra-wide band wireless sensor networks is left to the ingenuity of the ultra-wide band wireless sensors designer. In this article, we develop a novel one order complex-coefficient adaptive notch filter with a single zero-pole pair for in-band interferences suppression in cognitive ultra-wide band wireless sensor networks. The proposed algorithm only requires a single adaptive weight coefficient to notch out one narrow band interference. To cope with multiple in-band narrow band interferences simultaneously, a linear cascaded high order adaptive interference suppression and a novel cyclic cascaded high order matrix adaptive interference suppression scheme are also presented. The theoretical analysis and numerical simulation experimentation results indicate that the interference tolerance margin of time hopping based ultra-wide band wireless sensor networks can be greatly enhanced by the proposed complex-coefficient cyclic cascaded high order matrix adaptive filters, which have excellent suppression effects to in-band strong narrow band interferences in low-cost low-power-consumption cognitive ultra-wide band sensor networks with a substantial SINR promotion acquired. In addition, the proposed complex-coefficient adaptive in-band interference suppression processing can be executed before the demodulation module; it is also suitable for front end in-band interference elimination of the non-coherent impulse-based ultra-wide band wireless sensor networks connected with Rake receiver and multiuser detector.
# Optimizing the Quality of Service of Mobile Broadband Networks for a Dense Urban Environment
## 3 Experimental Design
### Drive Test Procedure  
The drive test procedure involved a test vehicle where the test equipment was installed. The setup was comprised of a GPS, a computer, and a terminal station. An average speed of 30 km/h was maintained to simulate traffic conditions. A terminal connection was established using the 4G LTE-compatible Huawei Modern E392. Upon a successful connection, the download of five files totaling 20 GB was initiated. Whenever the connection dropped, the simultaneous download was continued once the network was restored. Also important is adherence to the planned cluster during the drive test. All measured data from the different sites were then saved in appropriately named csv files and exported to MATLAB for analysis and optimization.
## 3 Manufacturing Techniques for Wearable Antennas
### Flexible Textile Wearable Antennas
#### 3.2.2 Woven or Knitted Conductive Sheets
The two layer antenna allowed an independent selection of the antenna substrate. Fleece fabric was selected for the antenna substrate because it has permittivity close to 1 and a low loss tangent which is optimal for the radiation efficiency. Felt was selected for the microstrip feed line substrate. Felt has a higher permittivity and by selecting a thinner material the radiation losses are restricted. A new design of a woven textile antenna covered with a protective cloth (e.g., waterproof, insulation) was presented in [32]. Finally a novel grid microstrip woven antenna design and fabrication method is presented in [33]. The substrate of the antenna was a 3D woven glass fiber fabric and the conductive yarn that used was copper yarn. The conductive yarns were orthogonally woven to produce a grid structure.
###### Abstract
Unlike the multi-time scale optimal dispatch method, Model Predictive Control (MPC) is widely used in uncertain optimal control problems of power systems due to its rolling optimization and feedback correction features. MPC is an effective approach to address an uncertain optimal dispatch about wind and PV [15]. To minimize the impact of wind forecast error on optimal dispatch, previous studies have combined multi-time scale optimal dispatch method with MPC. Reference [16] uses multi-time scales to achieve economic optimal dispatch of a micro energy grid. Reference [17] for optimal dispatch, uses particle swarm optimization to solve the day-ahead stage and adjust the results of the day-ahead stage using MPC for the intra-day. Compared with the traditional multi-time scale optimal dispatch method, combined with the model predictive control algorithm, the closed-loop optimization of the multi-time section can be realized through the prediction and feedback correction functions of MPC, and the actual state of the system can be fed back, reducing the influence of forecast error and external interference. Considering the above, the purpose of this study is to coordinate the active power and reactive power resources including VPSSH of the distribution network, to achieve the lowest operation cost and the minimum node voltage deviation of the distribution network, proposing a multi-time scale optimal dispatch method based on model predictive control. The proposed method includes two stages: day-ahead dispatch and intra-day rolling dispatch. The intra-day rolling dispatch adopts model predictive control, rolling updates the forecast information of wind, PV, and load, and feedback on the actual state of the system for optimization.
## 7 Research Limitations and Future Research Guidelines  
The study results have various limitations. First, the determinants are investigated initially from theoretical context greatly due to the nature of the published studies. The determinants are extracted from those identified studies which were conducted for SME, multiple companies, academic, healthcare, telecommunication, supply chain, retail and banking sectors. There might be different determinants for different industries that influence the firms' decisions to the BIS adoption in different contexts. Second, the current study presents a general theoretical framework that comprises the most frequently used theories, and models. There might be different theories and different frameworks that can greatly affect the particular business or industry for the BIS adoption. Third, the main objective of this review was to explore the significant determinants which can influence the organizations' intention to adopt the BIS conceptually. The analysis was performed on previously collected quantitative and qualitative studies results from theoretical context. Most of the studies were survey-based. There is a lack of case studies that are required to prove the current study findings more applicable in a practical way. In order to extend the current study results further, practical implementations are required by practitioners and industry experts. Fourth, biases could not be avoided in content analysis because of human interference in forced-set coding rules, the ambiguity of word meanings and textual analysis process, although, maximum efforts are made to make sure the results are more objective and minimize the biases. Therefore, the findings might reflect common phenomena from a theoretical perspective. Only 13.8% studies addressed the individual level acceptance of BIS. Researchers should consider and propose individual level theories and models such as motivation theory, social cognitive theory, stakeholder theory, and decision theory for the BIS adoption. RBV, Dynamic Capability View, and critical success factors (CSF) theories should also be considered before the adoption decision of BIS in organizations. These proposed theories will be helpful in identifying the important resources and capabilities that configure to build competitive advantage and will contribute to the successof BIS projects [99]. Lastly, this study has investigated the determinants comprehensively with theoretical lenses that were most influential for the BIS research area. However, it did not provide any relationship among determinants and their specific effect on success outcomes, such as the efficiency and effectiveness of the decision-making process. Further, research could employ a meta-analysis to extend the knowledge in this field.
## 3 System Design of the Intelligent System  
### System Integration  
Figure 2 shows the flow chart of the wireless fatigue monitoring system. The time history of the object's fatigue response is sensed by the sensing probe. The obtained data is transmitted to a strain amplifying processor, which achieves the digital-to-analog conversion to convert the time history into digital signal. The DSP module implemented with rain-flow counting method analyzes the signals, and the key parameters of fatigue features are acquired and saved in the DSP microchip and finally transmitted by the wireless transmitter module to the user PC. The fatigue damage is estimated using the acquired key parameters.
# Trends and Opportunities in the Dairy Industry: A2 Milk and Processing Methods
## 5 Milk Processing
### Non-Thermal Methods
#### 5.2.8 Membrane Technologies  
Membrane-based processes are microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), and reverse osmosis (RO). The capacity to regulate the permeability of ceramic filter membranes enables the utilization of these membranes for the separation of milk components, as well as for the separation of bacteria and spores. MF can fractionate fat globules (10 um) and remove bacteria and spores (1 um). UF can separate casein micelles (100 nm) or serum proteins (10 nm). When NF and RO are utilized, lactose (1 nm), salt (0.1 nm), and water can be recovered [122]. Filtering out micro-organism spores is very effective and, compared to other non-thermal methods, gives the best results, which can be compared to the effects of pasteurization [123].  
The industry uses multi-stage membrane filtration to extract separated protein or fat fractions (for example, MFGM), which is common in commercial dairy plants. These do not affect the components of the milk but only allow them to be purified or separated. Thisoffers the possibility of producing functional intermediates, such as protein-rich permeate streams, and the mentioned separation of micro-organisms [124; 125].  
Membrane separation technology is a revolutionary approach to isolating and purifying milk fat globules (MFGMs). The most common membrane separation techniques for MFGM isolation are microfiltration (0.1-1 \(\upmu\)m), ultrafiltration (0.001-0.1 \(\upmu\)m), and di-aliltration. The diameter of the whey protein (3-6 nm) is significantly smaller than that of the MFGM fragments (100-400 nm), allowing for their removal by filtration. Compared to traditional methods, membrane separation technology is highly effective in increasing the relative abundance of MFGM fractions and MFGM protein while reducing the presence of other molecules in the product [126].
# Road Pavement, Road Pollution, and Sustainability under Climate Change Increased Temperature
## 1 Introduction
### The Road Pavement as a Sink and Source of Road Runoff Pollutants
Several strategies are used to deal with road runoff pollution, such as the control at source (reduction of pollutants' emissions) or the construction of treatment systems that receive the runoff from the road and discharge it to the environment, with a reduced concentration of pollutants. The removal of solids and particulate pollutants are among the operations targeted in these treatment systems. [PERSON] et al. [50] indicate that around 80% of highway particles are <0.05 mm. [PERSON] et al. [51] report the difference between particles found at the road pavement surface and the ones that are likely to be washed out by rainfall events (smaller fractions). At least 55% of particles found at a highway and a parking lot surfaces were <0.6 mm. [PERSON] et al. (2021) [49] studied filter media removal of particles from road runoff and found that, according to several authors, they are predominantly present in the fine fraction (<63 \(\upmu\)m). [PERSON] et al. [45] studied the content of heavy metals (Cd, As, Cu, Cd, Hg, Ni, Pb, and Zn) in stormwater sediments, and assessed the correlation of metals to finer particle fractions. For instance, Cd was strongly associated with particles sized > 63 \(\upmu\)m and Cu to lower than 0.45 \(\upmu\)m sizes. [PERSON] et al. [34] and [PERSON] et al. [43] agree that the adsorption of metals to road particles < 63 \(\upmu\)m is most relevant, and that road sediment must be studied in order to prevent impacts in receiving waters and toxicity in the biota. [PERSON] et al. [52] studied tire and bitumen particles in several size ranges, from 37 up to 5000 \(\upmu\)m. The research showed that most of the tire and bitumen particles were from the size range from 37 to 300 \(\upmu\)m, and the tire particles were predominantly present in smaller sizes. [PERSON] et al. [53] present similar results for rubber, bitumen, and other microplastic particles in highway runoff--the higher concentrations detected were associated with particles size fractions of 100 \(\upmu\)m to 300 \(\upmu\)m.  
The adaptation of roads to climate change should be used to explore the performance of pavement materials and mix design innovation, as well as to combine it with pollution control strategies developing integrated solutions and responding to the challenges of sustainability. Research focused on the evaluation of the effects of temperature on bituminous mixture viscoelastic properties and its likeliness to affect particle retention at the road surface can contribute to new approaches for adaptation to climate change and for pavement sustainability.
# A Segmentation-Based Optimal Seamline Generation Method for SAR Image Mosaic
## 2 Materials and Methods  
### Overview  
The procedural flow of this paper is visually represented in Figure 1. In the initial phase, registration and radiometric normalization procedures are applied to multiple single-look complex (SLC) images, representing the essential radiometric and geometric preprocessing stage crucial for mosaic creation. In the initial seamline network established through the AVDO method [10], each seamline is generated solely based on geometry, resulting in paths that traverse numerous feature targets, and hence may not be optimal. Recognizing the challenges associated with pixel-based information and the difficulty of obtaining high-quality auxiliary data, an object-based method emerges as a suitable alternative for seamline generation. The proposed SOSG model initiates with the joint segmentation of SAR images, followed by the screening of homogeneous areas, the con struction of a cost matrix, and ultimately the generation of optimal seamless. The final steps involve mosaicking and image blending processes, culminating in the formation of a comprehensive mosaic image. This comprehensive model aims to overcome the limitations of pixel-based methods and enhance the effectiveness of seamline generation in SAR image mosaicking.
# Line Matching Based on Viewpoint-Invariance for Stereo Wide-Baseline Aerial Images
## 5 Discussion
### Applicability of Perspective Transformation Model to Other Line Matching Methods  
It has already been mentioned in the introduction that the current line matching methods mainly include similarity matching based on the photometric information of line segments' neighborhoods and geometric feature constraints, or matching based on a single line or lines group. The LJL method used in this paper belongs to the photometric, information-based matching approach, but also belongs to the lines group-based approach. It is analyzed and experimentally proven that the photometric information of line segments' neighborhoods is recovered in the rectified images after perspective projection, which is the main reason for the matching improvement. In fact, it is also effective for the method based on images' geometric feature constraints. This is because the relative geometric relationships among the various image features are also more realistic, and any constraint condition will be more accurate once an image is rectified as an orthomorphic image. It is the same for matching with a single line or lines group. Therefore, this method is equivalent to improving the image quality from the data source, and will inevitably improve the effect of various types of line matching methods.
## 2 Methodology
### Link Budget Analysis
#### 2.6.4 Airtime  
Time on air, or airtime, is directly related to the amount of data that can be transmitted over the wireless channel within a given time period. The more airtime that is available, the more data that can be transmitted. To optimize the use of airtime in wireless networks, various techniques are used, such as dynamic channel allocation, adaptive modulation and power control. These techniques help to minimize interference and increase the efficiency of data transmission, thereby improving the overall performance of the link margin. Airtime is the time it takes for the signal to reach the receiver on the satellite from the ground terminal. Equation (14) is used to calculate airtime [43].  
\[Airtime\ (s)=\frac{2^{SF}}{BW}\ *\ Tot\ frame\ length \tag{14}\]  
\[Tot\ frame\ length(symbols)=n_{payload}+n_{preamble}+4.25 \tag{15}\]  
where \(n_{payload}\) is the payload length that is expressed in Equation (16) and \(n_{preamble}\) is the preamble length.  
\[n_{payload}=8+max(ceil(\frac{(8\ *\ Payload\ length-4\ *\ SF+28+16)}{SF})\ *\ ( \frac{1}{CR}),0) \tag{16}\]
# Transmission Delay-Based Uplink Multi-User Scheduling in IEEE 802.11 ax Networks +
## 2 Related Work
### Multi-User Transmissions in IEEE 802.11 ax
They investigated the benefit of utilizing multi-user transmissions scenarios under the channel sounding process specified in IEEE 802.11 ax, and suggested adjusting the contention window size to further improve throughput performance by avoiding collisions between AP- and user-initiated transmissions. [PERSON] et al. presented cooperative control methods for uplink multi-user transmissions in IEEE 802.11 ax networks [15]. The first method involves adjusting th spatial reuse parameters. The second method involves scheduling stations using hierarchical clustering, in which basic service sets whose mutual interference is small are clustered together. [PERSON] et al. studied a multi-user spectrum access method for IEEE 802.11 ax-enabled stations [16]. In IEEE 802.11 ax networks, stations may access the network by randomly selecting a subchannel among the available subchannels. The authors applied convolution neural network (CNN)-based deep reinforcement learning for selecting the subchannel. Each station locally trains its CNN based on the energy detection of channels and ACK packets without requiring centralized training. The above works focused on balancing the AP-initiated multi-user transmissions and user-initiated transmissions with a back-off process for channel access, increasing transmission success probability by spatially clustering the stations with APs, or increasing channel access probability of stations using channel learning techniques. In this study, we focused on the scheduling of uplink multi-user transmissions in a dense IEEE 802.11 ax network. The proposed method enhances channel use by clustering stations with similar transmission delays for uplink multi-user transmissions in a network where a large number of stations are deployed.
# A Cloud Microservices Architecture for Data Integrity Verifiability Based on Blockchain
## 8 Validation and Proofs
### System Complexity  
We carried out some tests with respect to the amount of resources required to run the storing and consulting services. The tests were latency and processing time. Latency is the time any supply chain microservice takes to reach its destination and return, taking into account an HTTP request. The processing time is the time in milliseconds (ms) that the API Gateway takes to execute a request since it arrives until it is processed and returned to the requester. Table 7 shows some details of one of the runs. The first column states the stage of the cloud supply chain microservice from where the request was established. The following three columns state the transaction latency (_Start_, _End_) that the request takes (_Time_) to reach its destination and return to the microservice. The fifth column pinpoints the HTTP method executed (POST, PUT, DELETE, or GET). The next three columns state the processing time within the Event API-Server. The last column is a brief description about the type of request. Note that _Start_ and _End_ columns are expressed in epoch Linux time, and column _Time_ is expressed in milliseconds, being it the difference between _End_ and _Start_.  
We can analyze that methods POST, PUT, and DELETE, which correspond to storing information within the blockchain, are very similar and took 6646 ms latency on average, respectively, a 1768 ms processing time. On the other hand, consulting information took 2516 ms latency on average, respectively 979 ms in processing time. These statistics could oscillate using another blockchain platform. The average transmission rate from the microservices was a 1.91 Mbps upload and 29.78 Mbps download.