esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Model Results
#### 3.2.2 Factor Importance  
Figure 4 illustrates the estimated SHAP values of the study's XGBoost model. It indicates the importance and direction of independent variables in determining if a certain area is likely to be urbanized or not.  
First of all, the distance to nearest forest area was found to be the most influencing factor. The XGBoost model of this study showed that the probability of urbanization increases as the distance to nearest forest area increases. Second, the topographic features, including slope and elevation, also showed relatively high significance to urban expansion. Both factors were negatively associated with the urbanization of a certain area. Those findings suggest that the physical availability of development is the most influencing factor on urban expansion [5,43].  
Socioeconomic features were also found to be relatively significant predictors of urban expansion. The GRDP per capita and population density of a certain region tend to accelerate the development of the nearest urban area. It is notable that the economic vitality is a more important factor of urbanization, compared to the population number.  
On the other hand, the distance from existing urbanized areas did not significantly affect the level of urban expansion, particularly for residential and commercial areas. Instead, the distance from the nearest industrial and transportation areas was found to be negatively associated with the possibility of urbanization.  
In terms of environmental features, the legislative ECVAM grade was a more significant predictor of urban expansion than the ecological ECVAM grade. This outcome makes sense in that the legislative ECVAM grade is based on several legal restrictions of the land development, while the ecological ECVAM grade only recommends consideration for development without coercion [47,48]. As both legislative and ecological ECVAM grades increased, the possibility of urban expansion also increased.
## 4 Functionality Demonstration of the Mission Design Configurations in the ISL Network
### Demonstration of Signal Time Delay Detection and Mission Determination
Also, the delay between a rising and a falling edge of the two 1 PPS signals, d, was observed as 0.2 s.  
When Sat \(A\) transmits SS signals to Sat \(B\), the superimposition of these time stamps could be visualized on the received signal as shown in Figure 14.  
Four data frames recorded for 4.85 s were observed. This simulation was performed at 400.15 MHz at 500 KSPS. The superimposed fixed time delays of \(\delta T\) = 0.3 s and d = 0.2 s, which represent the influence of _TWVC_ and _TEC_, were observed on the received data frames. Even though the delays provided by the delay pulse generator were fixed irrespective of frequency change, when the delays were tuned up and down, the variation of the delay change was observed in the data. This proved the efficiency of this system in detecting time delay in orbit where frequency change has an impact on atmospheric geophysical parameters. From the simulation results, the transmitted SS data could also be decoded perfectly even with a delay. For an in-orbit scenario, since _TEC_ is inversely proportional to the radio frequencies, the 400.15 MHz frequency is anticipated to give a higher resolution of the measurement values compared to the 460.00 MHz. _TWVC_ and _TEC_  
Figure 14: Results of the test with delay pulse generator at 400.15 MHz. Figure 13: GPS 1 PPS pulse (yellow) and a delay pulse (blue) output of delay pulse generator. difference values are computed with processing algorithms. Finally, _TWVC_ can be deduced following Equations (1)-(9).
## 5 IETF ROLL Working Group
### Implementation and Evaluation
#### 5.2.8 General Performance  
For the implementation of RPL in Contiki, according to [48], 3224 bytes of the ROM are used and 800 bytes of the RAM. For a Tmote Sky note this implies 6.5% of the ROM- and 8% of the RAM-resources.  
The usage of the Trickle timer helps to minimize the amount of routing overhead. In a stable network the Trickle timer allows the beacon intervals to exponentially increase and when noticeable changes in the network conditions are detected the beacon interval quickly decreases to the minimum interval. Still, for scenarios with bidirectional traffic, the RPL protocol generates a larger traffic overhead (albeit with comparable delivery ratios) when compared to a protocol like LOAD [69]. It also has to be noted that LOAD is a reactive protocol, which has the additional advantage that the overhead is dependent of the traffic load, while RPL is proactive and has a constant overhead. When comparing TinyRPL with CTP [70], the well-known point-to-sink routing protocol for TinyOS, simulations indicate that the performance of both protocols has a comparable packet reception ratio and overhead. The benefit of RPL, compared to CTP, is the support for various types of traffic patterns (_i.e._, multipoint-to-point, point-to-multipoint and point-to-point traffic) and the ability to directly connect to Internet nodes.  
Finally, [71] analyzes the performance of RPL based on different simulations and concludes that RPL can ensure a fast network setup, which makes it a candidate protocol for monitoring applications in critical conditions. However they conclude that optimizations are required concerning the signaling in order to decrease protocol overhead.
# Automatic Configurable Hardware Code Generation for Software-Defined Radios+
## 9 Related Work
### Frame-Based DSL for SDR  
[PERSON] et al. [28] present a frame-based Domain Specific Language (DSL) for prototyping SDRs on FPGAs and the DSL is available as open-source to enable further research in the SDR community. The DSL design flow uses the SDF model to connect the IP components and to communicate frame information among the network components. Furthermore, it supports high-level HLS optimizations and enables the re-use of defined components. The disadvantages of these DSL are that it only supports frame-based applications such OFDM systems, it does not formally bridge the semantic between the SDF model and the generated hardware designs, and lastly the SDF model does not use the access patterns which are necessary for correct and optimized designs.
# Applications of Probabilistic Forecasting in Smart Grids: A Review
## 6 Decision Making under Uncertainties  
The future power system is heading towards being smart and decentralized. In a new smart grid system, there will be a number of agents and stakeholders that face uncertainties in their decision-making problems. Here are some examples:  
* A generation company that has renewable resources needs to submit offers to energy markets before knowing the resources' exact generation and market prices.
* Every management system in smart grids (such as microgrid energy management system and energy community management systems) needs to deal with its intermittent renewable energy resources' output as well as the uncertain resources' behavior (such as the EV charging behavior) to come up with the optimal scheduling and management of resources.
* Strategic agents try to deal with uncertain market prices and their competitors' strategies beforehand when they construct their optimal bidding strategies.
* Retailers should buy electricity based on their customers' uncertain demand.
* Balancing responsible parties require to schedule their flexible energy resources, such as their energy storage systems, based on the uncertain generation in a way to maintain the balance between their generation and their demand.
* Transmission system operators (TSO) and distribution system operators (DSO) must decide on the amount of reserves and flexibility as well as the methods to operate their network and keep the security of supply and reliability of the system within the specified limit, in spite of different uncertainties and the intermittency of renewables.  
Hence, the lack of perfect information affects optimal decision making. In this regard, stochastic programming, robust programming, and chance-constrained models offer to solve optimization problems with uncertain input data.
## 2 Proposed Methodology for Industrial Electric Load Identification
### Data Introduction  
To evaluate the practicability of the proposed method in a realistic industrial scenario, the data from an actual Chinese cement plant were used in the experiments. Active power (P) and reactive power (Q) were collected at a sampling frequency of 1/300 Hz for each piece of equipment in the plant. The data were collected over the time span from September to November. Nine pieces of industrial equipment were selected for the study, and P and Q of the electrical equipment were used as input information. For 90 days of power data, the data were first divided by the basic time unit of 24 h. Then, the equipment power data were combined into data samples. Finally, the power dataset of the nine pieces of standard industrial electric equipment was formed. The authors abbreviated these nine units as follows: exhaust gas treatment exhaust motor (ETE), roller press motor (RPM), coal mill wind motor (CMW), coal mill main motor (CMM), cement mill exhaust motor (CME), cement mill main motor (CEM), cement circulating air motor (CCA), kiln head induced air motor (KHI), and kiln tail high temperature air motor (KHT). Unlike the public dataset in residential power scenarios, the sampling frequency of industrial scenarios in reality is very low, which leads to poorer quality of raw power data and more difficult identification of power loads.  
The experimental data in this paper were from a real plant, so they contained many abnormal values. These anomalous data may have come from equipment failures or human error. However, the raw power data served as a valid basis for the experiment, and the presence of anomalous values may have caused the experiment to seriously deviate from  
Figure 1: Flow chart of the specific implementation process in this paper.  
the real results. Therefore, the data should be cleaned and denoised before the experiment to improve the data quality. According to research on industrial equipment, the load profile of industrial equipment has the following characteristics: firstly, the overall load profile changes smoothly over time and usually does not change abruptly; secondly, the industrial load profile is related to the production planning, and the adjacent dates when the equipment works should have similar load patterns. Considering the above, this paper preprocessed the dataset by replacing abnormal values, filling in missing values, and removing invalid dates.
# A Review: Image Processing Techniques' Roles towards Energy-Efficient and Secure IoT
## 8 Future Trends
For IoTSs requiring the transmission of multi-frame images via IoT networks, a solution to this problem is to provide a system that prioritizes the transfer of particular frames depending on analysis decisions made by image processes. Images containing significant content will be uploaded to the cloud [45];
* Another important barrier to image processing in the setting of IoT-implemented systems is connected to the security of the communication channel between the source of image processing and the destination. Because of the importance of transferring digital material while maintaining the safety of the communication route, this problem is still difficult to solve. Hence, presently proposed studies are tackling this problem by observing that the security system is essential to reach a high degree of lightweight;
* In accordance with [57], a smaller image is better for IoT-cloud image transfer. The data size across IoT communication channels will be decreased as a consequence, helping to minimize overall energy usage. This will contribute to shifting energy-friendly IoT seeking to realize the vision of the development of sustainable energy. One of the future trends towards sustainable energy in the IoT environment is to use effective security schemes that serve to considerably decrease the size of the image to minimize both transmission time and size;
* One method for increasing the security of images stored in the IoT cloud or on other servers is to divide them into blocks of images, which may be used to create a double-phase security scheme for images;
* Embedding a password mechanism should have helped the attainment of the integrity target of encrypted medical images [64]. As long as you embed an OTP in the encrypted medical image, the authorized person may verify the embedded OTP by comparing it to another OTP that was transmitted via a secure channel.
# Behavioural Analysis of Dogs' Response to Threatening and Neutral Conspecific Video Stimuli +
## 2 Materials and Methods
### Video and Audio Stimuli  
The video stimuli were recorded (with an iPhone 12, video setting 4 K, 60 fps) from two female dogs: Dog 1--an 8-year-old Weimaraner (neutered) and Dog 2--a 2-year-old Rhodesian Ridgeback. The two dogs were comparable in size and morphology. The recording of the videos was performed in an outdoor fenced yard where the dogs were held on a leash in front of a black sheet (placed to cover the human handler) and a camera was placed on a tripod in front of the dog. The use of two spontaneous reactions in a natural context, together with the choice not to train the tested dogs to look at the screen during the test were made to maximise the ecological validity of the stimuli presented and the spontaneity of the subjects' reactions. Four videos were recorded:  
* Threating videos in which both Dog 1 and Dog 2 (individually) were recorded on a front-facing camera while standing and barking at another unfamiliar dog walking by a fence: Dog 1 Threating (D1T) and Dog 2 Threating (D2T).
* Neutral videos in which both Dog 1 and Dog 2 (individually) were recorded using a front-facing camera while standing and panting without showing any threatening behaviour: Dog 1 Neutral (D1N) and Dog 2 Neutral (D2N).  
The two videos recreated a natural context in which dogs either showed threatening/aggressive behaviours and vocalization (barking) or neutral behaviours and vocalization (panting); the videos were intended to both have auditory cues, and panting for  
Figure 1: Schematic representation of the room and experimental set up, (A) projector, (B) dark green panels and white dashed line on the floor, visually delimiting the space inaccessible for the dog, (C) projector screen, (D) speaker, (E) water.  
thermoregulation on a warm day was chosen as the neutral auditory cue. The dogs panting during the neutral videos were not previously subjected to physical exercise or any type of distress.  
From the videos, 7 s were extracted (Final Cut Pro 10.6.2 optimised for M1) (See Video study in the Supplemental Material). The sound of the videos was extracted and filtered to eliminate background noises (edited with Adobe Audition-version 2022). To reproduce the barking and the panting realistically during the experiment, we measured the sound level (with a sound level meter, model SLM-25 SoundLevel: 30-130 dCB) of the same dogs (Dog1 and Dog2) barking and panting inside the testing room. The bark measured ~90-105 dCB while the panting measured ~70-85 dCB. The volume of the videos was then set at a level that allowed the sound level meter to measure the same dCB level as the real dog barking and panting in the room.  
The dogs tested may have reacted only to the sounds of panting and barking, independently of the visual stimuli [27]. To control for the possible effect of the sound on the reaction of the dogs tested, the same videos were paired with artificial sounds (pink noise) with the same characteristics (Hz, amplitude and pattern) as the original sounds (generated by Adobe Audition-version 2022).
# Designing Procedure Execution Tools with Emerging Technologies for Future Astronauts
## 5 Just-in-Time Training
### Prototype  
The prototype developed takes advantage of the Microsoft HoloLens to display information to the user. The HoloLens is a hands-free AR HMD that uses gesture and voice to make selections and commands. This AR form factor is considered ideal (as opposed to hand-held mobile AR) for future astronauts as they often need both hands to complete complex procedures. Our prototype used fixed-placed holograms that provide relevant information near a specific hardware or location, as well as procedure instructions which stay in view and follow the user's movements (see Figure 8). While we were able to collect a large amount of information from the environment (such as the user's progress in the procedure and their proximity to tools), only the most relevant information was presented to the users so as to not overload them. We found that the HoloLens's small field of view also constrained the amount of information we could communicate at one time.  
We embedded IoT sensors in the tools we required participants to find and on a wristband that participants would wear as they completed our task (see Figure 9b). The IoT sensors used in our prototype were based on an ESP8266 chipset which were powered by small lithium batteries. This chipset was then attached to each tool which allowed us to provide information on location, orientation, and movement. Each of these chips was equipped with an accelerometer as well as a light-emitting diode (LED) and had the ability to communicate back and forth to a central server. In order to determine locations of the chipsets embedded on our tools we used a Wi-Fi transceiver to provide a rough estimate of distance between objects. This relative signal strength identification can continuously perform scans which provide real-time location information. This location information allowed us to instantiate holograms within the headset at specific times and locations  
Figure 8: Holographic animations of the rodent research habitat showed users how to complete the task.  
within the study. The connected IoT network paired with the HoloLens enabled us to reveal and remove relevant information when it was needed. As an example, we used the HoloLens to indicate and guide the user to tools that they were tasked with finding, identify when the tools were picked up using the accelerometer data collected by each tool, and then update the interface to move users onto the next step in the usability study. Showing and hiding salient information was a requirement because of the limited field of view within the HoloLens and the large amount of information we were trying to communicate like tool location, procedure steps, and holographic overlays (see Figures 8 and 9a).
## 3 Results
### Supplementation of Ex-Situ Biofloc in Shrimp Grow-Out Culture at Low Salinity Conditions
#### 3.1.2. Shrimp Growth Performance  
At six weeks culture period, supplementation with ex-situ biofloc significantly increased the survival and growth of the shrimp (Table 2). Survival rates of shrimp-fed with commercial pellet (100%C) were significantly lower than shrimp-fed with 5% and 10% pellet reduction supplemented with 0.3% ex-situ biofloc (95%C+BF and 90%C+BF). In addition, gained weight, gained length, and specific growth rate of shrimp-fed with 95%C+BF and 90%C+BF were significantly higher than those of shrimp-fed with 100%C. Results indicated that microbial community in the ex-situ biofloc may have a role as a feed supplement to improve shrimp growth performance.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Shrimp Growth Performance** & **100\%C** & **95\%C+BF** & **90\%C+BF** \\ \hline Survival (\%) & 53.33 \(\pm\) 5.94 \({}^{\text{a}}\) & 83.81 \(\pm\) 3.30 \({}^{\text{b}}\) & 85.71 \(\pm\) 7.56 \({}^{\text{b}}\) \\ Gained weight (g) & 0.86 \(\pm\) 0.15 \({}^{\text{a}}\) & 1.97 \(\pm\) 0.14 \({}^{\text{b}}\) & 1.89 \(\pm\) 0.29 \({}^{\text{b}}\) \\ Gained length (cm) & 4.57 \(\pm\) 0.52 \({}^{\text{a}}\) & 6.82 \(\pm\) 0.13 \({}^{\text{b}}\) & 6.92 \(\pm\) 0.22 \({}^{\text{b}}\) \\ Specific Growth Rate (SGR) (\%/day) & 6.59 \(\pm\) 0.50 \({}^{\text{a}}\) & 8.31 \(\pm\) 0.28 \({}^{\text{b}}\) & 8.45 \(\pm\) 0.71 \({}^{\text{b}}\) \\ Biomass (g/m\({}^{3}\)) & 246.81 \(\pm\) 67.17 \({}^{\text{a}}\) & 851.63 \(\pm\) 86.79 \({}^{\text{b}}\) & 826.55 \(\pm\) 44.00 \({}^{\text{b}}\) \\ \hline \hline \end{tabular}
\end{table}
Table 2: Shrimp growth performance with and without supplementation of ex-situ bioflocs (100%C) and with different feeding regimes in which 95%C+BF were shrimp fed with 5% (\(w/w\)) feed reduction supplemented with 0.3% (\(v/v\)) biofloc, and 90%C+BF were shrimp fed with 10% (\(w/w\)) feed reduction supplemented with 0.3% (\(v/v\)) biofloc. Different letters above the values indicate significant differences among the treatments (\(p\) < 0.05).  
Figure 2: Concentrations of ammonia (**a**), nitrite (**b**), nitrate (**c**) and orthophosphate (**d**) concentrations during 6 weeks (W1-W6) of experiment using commercial pellet treatment without biofloc supplementation (100%C; blue), 5% (\(w/w\)) feed reduction supplemented with 0.3% (\(v/v\)) biofloc (95%C+BF; red) and 10% (\(w/w\)) feed reduction supplemented with 0.3% (\(v/v\)) biofloc (90%C+BF; yellow). Error bars represent a value of \(\pm\)standard derivation. An asterisk represents a significant difference among the three groups at particular time point (\(p\) < 0.05).
# Screening Mechanism and Properties of a Cantilevered Vibrating Sieve for Particles Processing
## 3 Screening Mechanism of Cantilevered Vibrating Sieve (CVS) Based on Motion Characteristics
### Anti-Plugging Mechanism of Cantilevered Vibrating System (CVS)  
As analyzed above, the CVS has a higher opening rate and fewer constraints to sieve rods compared to traditional vibration screens. Besides this, if the screen body is manually set to oscillate at a vibration frequency around the natural circular frequency of cantilevered sieve rod, a large additional bending vibration will be produced to eject the plugging material on the sieve. Hence, the anti-plugging mechanism of a CVS can be summarized and is displayed in Figure 4. During a material feeding process, the oversized product hits against the sieve rods when moving along the sieve rods from the feeding end to the discharge end. Such impact induces an external outward pull to crack the clusters of wet-sticky particle swarm. Moreover, the cantilevered sieve rods may also experience a longitudinal shift to yield a larger space for near-aperture particles rubbing motion. This further accelerates the subsidence and lateral motion of particle then reduces the sieve plugging.
## 3 Data and Methodology
### Explanatory Variables
#### 3.2.2 Land-Use Variables  
Land-use variables are obtained through Baidu's open platform, including different POI categories, such as metro stations, tertiary hospitals, large shopping centers, parks, schools, and commercial districts ([[http://lbsyun.baidu.com/](http://lbsyun.baidu.com/)]([http://lbsyun.baidu.com/](http://lbsyun.baidu.com/)) (accessed on 20 February 2025)). POIs are generally regarded as key indicators of urban land-use functions and thus represent built-environment diversity [73]. This study classifies the collected POI data into 14 categories to capture the functional distribution of different urban areas. However, because the quantity of POIs varies considerably across categories, simply counting the number of POIs could lead to significant errors. Instead, this study uses Enrichment Factors (\(E\)Fs) within each grid cell rather than the density of POIs to represent local land-use characteristics. \(EF\) serves as a normalized measure that mitigates the imbalance in the distribution of POIs among categories, thus more accurately reflecting real land-use functions [88]. The \(EF\) value is calculated by comparing its local proportion to the overall proportion, as shown in Equation (1).  
\[EF_{j}=\frac{N_{j}^{i}/N_{j}}{N^{i}/N} \tag{1}\]  
where \(i\) refers to \(i\)th POI category, \(j\) refers to the \(j\)th analysis grid, and \(N\) refers to the total number of POIs.