esa-sceva/satcom-chunk-collection huggingface dataset:
# Towards Automatic Image Enhancement with Genetic Programming and Machine Learning
## 3 The Proposed Approach  
The objective of this work is the development of an adaptive IE system, and its application on real estate pictures, as part of the collaboration with the Spanish company _PhotoLike_. We had access to datasets addressed in Section 4.2 and to an objective image qualification software for real estate images. This section will discuss how we approached the development of a solution to the real estate problem.  
Looking at the information shown previously in Section 2, the Evolutionary- and Machine Learning-based approaches can produce models that better adapt to different kinds of inputs. Our research also shows that global enhancement, meaning the simultaneous enhancement of multiple features of an image, is a challenging goal to achieve, as the solution space of an IE solution is vast. Common approaches to automatic IE focus on individual and more straightforward tasks, such as color balancing, in order to prevent over-enhancement where an image becomes too far-off from the original one, losing important context-sensitive information.
## 3 Results and Discussion
### Electrochemical Properties
The rate performances of MgCo\({}_{2}\)O\({}_{4}\)calicinated at various temperatures are tested in 0.01-3.0 V at different current densities of 200, 500, 1000, and 200 mA g\({}^{-1}\), as shown in Figure 4d. At the current density of 200 mA g\({}^{-1}\), the reversible capacity of MCO-600 was 968.5 mAh g\({}^{-1}\), while the reversible capacities of MCO-500, MCO-550, and MCO-650 were 921.7, 962.8, and 899.9 mAh g\({}^{-1}\), respectively. With the increase of the current density, their reversible capacities were decreased. The MCO-600 anode can still deliver 965.3 and 732 mAh g\({}^{-1}\) when the current density increased to 500 and 1000 mA g\({}^{-1}\), respectively, which is higher than the anodes prepared from MCO-500, MCO-550,and MCO-650. For example, the corresponding reversible capacity of MCO-650 anode was 853 and 684.3 mAh g\({}^{-1}\). The better rate capability of MCO-600 anode may be attributed to unique nanosheet structure, facilitating fast Li\({}^{+}\) diffusion and transportation. Figure 4e shows electrochemical impedance spectroscopy (EIS) of MgCo\({}_{2}\)O\({}_{4}\) tested ranging from 100 kHz to 0.01 Hz before cycling. The resistance of MCO-600 battery (70.3 \(\Omega\)) is much smaller than those of MCO-500 (510 \(\Omega\)), MCO-550 (605 \(\Omega\)), and MCO-650 batteries (200.1 \(\Omega\)), which is consistent with the superior cycling performance and cycling capability of MCO-600 anode. When the MCO-600 anode cycled for another 50 cycles, as shown in Figure 4f, the reversible capacity became stable and slightly decreased with the cycle number increased. After 100 cycles, the reversible capacity of MCO-600 was 1130.1 mAh g\({}^{-1}\) at a current density of 200 mA g\({}^{-1}\), and the corresponding retention rate is-96.3%, demonstrating good cycling stability of the MCO-600 anode. Figure 4: The electrochemical performances of MgCo\({}_{2}\)O\({}_{4}\): (**a**) the initial four CV cycling curves of as-prepared MCO-600 at 0.5 mV/s ranging from 0.01 V to 3.0 V; (**b**) the initial three galvanostatic charge-discharge curves of MCO-600 at 200 mA g\({}^{-1}\); (**c**) cycling performances of MgCo\({}_{2}\)O\({}_{4}\) prepared at various temperatures; (**d**) rate capability of MgCo\({}_{2}\)O\({}_{4}\) prepared at various temperatures; (**e**) the Nyquist plots of MgCo\({}_{2}\)O\({}_{4}\) prepared at various temperatures; (**f**) long cycling performances of MCO-600 at 200 mA g\({}^{-1}\) ranging from 0.01 V to 3.0 V.
## 4 Implementation
### Used Hardware
#### 4.1.2 DHT22 Humidity and Temperature Sensor  
In our proposed approach, we used DHT-22 (also known as AM2302) sensor as given in Figure 6, for detection of external environment temperature and Humidity. DHT-22 is a digital-output sensor. DHT-22 use thermistor to measure the surrounding environment and a capacitive humidity sensor. DHT-22 provides more accurate sensing capacity over large range as compare to DHT-11. Technical details of DHT-22 described given.  
* Power--3-5 V
* Max Current--2.5 mA
* Humidity--0--100%, 2-5% accuracy
* Temperature--40 to 80 \({}^{\circ}\)C, \(\pm\)0.5 \({}^{\circ}\)C accuracy
## 2 Related Works  
### MSIMP Basic Mission Scenarios  
MSIMP aims to coordinate multiple satellites for efficient imaging of target areas by optimizing satellite resources and time allocation. Firstly, the mission requirements and satellite resources of MSIMP are analyzed to determine the satellites to be observed and the mission information. It is assumed that \(N_{Target}\) observation mission \(\{Target_{i}|i=1,\ldots 6\}\) is performed by a set of satellites \(\{sat_{j}|j=1,\ldots 3\}\) at a certain regional scale, with a satellite executable orbit of \(\{Orbit_{k}|k=1,\ldots,3\}\). Each observation mission has multiple visible time windows \(w=\left\{w^{i,g}_{sat}\right\}|j\in sat,i\in Target,g\in window\right\}\) with multiple satellite resources, and each satellite resource is capable of performing multiple observation missions. Secondly, a mission planning solution algorithm is used to obtain the optimal MSIMP mission planning scenario within the mission planning time \([plan_{start},plan_{end}]\). This includes the assignment sequence and the visible time window planning scenario. The basic MSIMP mission scenario is shown in Figure 1.  
Figure 1a shows the sequence of multi-satellite imaging mission assignments, specifically \((Sat_{1},Target_{1},Target_{2})\), \((Sat_{2},Target_{3})\), and \((Sat_{3},Target_{5},Target_{6})\). Figure 1b shows the visible time window allocation scheme for each satellite and the target task, in which the blue rectangle represents the visible time window for the satellite, the gray rectangle represents the visible time window for the observation task, and the yellow rectangle represents the observation time window for the satellite to the target task. The specific time window allocation is \((Target_{1},[s_{1}^{1,1},et_{1}^{1,1}])\), \((Target_{2},[s_{1}^{1,2},et_{1}^{1,2}])\), \((Target_{3},[s_{2}^{2,3},et_{2}^{2,3}])\), \((Target_{5},[s_{1}^{3,5},et_{1}^{3,5}])\), and \((Target_{6},[s_{1}^{4,3},et_{3}^{3,6}])\), where \(st_{g}^{j,i}\) and \(et_{g}^{j,i}\) represent the start and end times of observation mission \(i\) in the \(g\)-th time window on satellite \(j\), respectively. Finally, the satellite performs corresponding assigned tasks according to the mission planning scheme, further evaluates the implementation effects of the tasks, and makes corresponding adjustments to the follow-up mission scheme according to the evaluation results [39; 40].
## 2 Materials and Methods
### System Description  
The wireless sensing platform proposed in this study consists of two key components: a centralized gateway implemented as the server socket and end nodes implemented as client sockets. The gateway is deployed on a Raspberry Pi 4 (RPi4), whereas the end nodes utilize Raspberry Pi Zero 2W (RPi0-2W) devices. Each individual end node is responsible for initiating a single client connection.  
In accordance with the discussion in Section 2.2, socket programming serves as the foundational framework for wireless communication, forming the backbone of the pro posed system. Furthermore, the client sockets implemented on RPi0-2W devices are equipped with ADXL345 MEMS sensors and a DS3231 RTC module. The selection of the Raspberry Pi Zero 2W is driven by its compact size, microSD card slot, and versatile wireless capabilities, which include Bluetooth and WiFi. These inherent features empower the client sockets not only to collect data but also to store it locally, distinguishing them from conventional MicroController.
## 8 Conclusions  
In this study, we introduced the model that use to solve the quasi-static problem of general spatial CDPM based on our simplified quasi-static model of a single cable. The explicit function that expresses the relationship between unstrained length \(L\) and tension exerted on free extremity \(\mathbf{B}\) along the \(X\)-axis \(T_{x}\) is also concerned and applied to solve the inverse kinematic problem of CDPM. The main motivation of employing our model is that it is applicable in real-time and has a low mean positioning error. However, we cannot control the accuracy of the position of the moving platform due to an undefined feasible wrench workspace. Furthermore, the relation (48) is valid for as long as \(T_{x}>T_{x_{\text{min}}}\). Thus, for a better version, we propose some future work:  
* Analyzing and determining the boundaries of the wrench-feasible workspace in order to determine the set of all wrenches that CDPMs can apply without violating the boundaries of the tensions and load capacities of actuators;
* Due to the presence of unstrained cables and large inertia of the moving platform, the vibration is easily identifiable in CDPM. Vibration has a great impact on the dynamic behavior of the positioning accuracy and deviation on force distribution. Therefore, having a good analysis of vibration is a premise to developing a good dynamic model.  
Conceptualization, N.T.T.; methodology, N.T.T.; software, P.G.L.; validation, P.G.L.; formal analysis, P.G.L.; resources, N.T.T.; data curation, P.G.L.; writing--original draft preparation, P.G.L.; writing--review and editing, P.G.L.; visualization, P.G.L.; supervision, N.T.T.T.; project administration, N.T.T.; funding acquisition, N.T.T.T. All authors have read and agreed to the published version of the manuscript.  
This research was supported by Ho Chi Minh City University of Technology and Education, Vietnam.  
The authors declare no conflict of interest  
Figure 27: Set of static poses and the positioning error of the moving platform illustrated by the size of each point.
## Materials and Methods  
### Resistance of the Step Structure  
Figure 1 shows the schematic diagrams of the step structure. The PSG layer is etched to produce a trench. The polysilicon layer is deposited to cover the trench surfaces and patterned to form the step structure. A single constant sticking coefficient, \(S_{rc}\), was found to be sufficient to describe the polysilicon deposition process for a given set of deposition conditions. When \(S_{rc}<0.01\), which is typical of silane-based polysilicon depositions, the distribution of the adsorbed concentration is uniform and the step coverage is conformal [22]. Figure 1a is the 3-D view of a step structure. It is a U-shaped structure with two horizontally extended arms. The width of the structure is \(w\). As displayed in Figure 1b, the resistance of the step structure consists of four parts: the resistance of the arm (\(R_{a}\)), the resistance of the bottom (\(R_{b}\)), the resistance of the sidewall (\(R_{sw}\)) and the resistance of the corner (\(R_{c}\)). According to the law of resistance, the resistance of the step structure (\(R_{step}\)) can be written as  
\[R_{step}=\frac{2R_{S}l_{a}}{w}+\frac{R_{S}(l_{b}-2\varepsilon)}{w}+\frac{2R_{ S}(t_{2}-t_{1})}{w\sin\theta}+4R_{c}, \tag{1}\]  
with  
\[\varepsilon=\frac{t_{2}-t_{1}}{\tan\theta}+\frac{t_{1}}{\sin\theta}, \tag{2}\]  
where \(R_{S}\) is the sheet resistance of the polysilicon layer, \(t_{1}\) and \(t_{2}\) are the thicknesses of the polysilicon layer and the PSG layer, respectively, \(l_{a}\) represents the length of \(R_{a}\), \(l_{b}\) denotes the designed length of the PSG trench, \(\theta\) stands for the sidewall etch angle.  
The method used to calculate the resistances of corners (\(R_{c}\)) is that of conformal transformations. The given pattern is transformed into a pattern with an obvious solution and then transformed back again to solve the desired problem [23; 24; 25]. Figure 2a shows six possible patterns of corners. The resistance of the corner is expressed as [24]  
\[R_{c}=\lambda\frac{R_{S}t_{1}}{w}, \tag{3}\]  
in which \(\lambda\) is the correction factor due to various shapes of the corners. As discussed extensively in [23; 24], the correction factors for corners of type A, type B, type C, type D, type E and type F illustrated in Figure 2a are estimated to be (0.57 \(\pm\) 0.01), 0.583, 0.317, \(-\)0.882, 0.559, and (0.341 \(\pm\) 0.005),respectively. Figure 2b is a SEM photo for the cross-section view of a step structure manufactured by a standard surface micromachining process. It is observed that the resistances of top corners and bottom corners of the step structure can be approximately estimated by corners of type B (\(R_{c}=0.583R_{S}\cdot t_{1}/w\)) and type E (\(R_{c}=0.559R_{S}\cdot t_{1}/w\)), respectively.
# Deep Learning-Based Cyclic Shift Keying Spread Spectrum Underwater Acoustic Communication
###### Abstract
Moreover, a water tank experiment was carried out, and some suggestions for future experiments are provided according to the analysis of experimental data. The rest of this paper is organized as follows. In Section 2, the structure of the conventional CSK-SS UWA communication system, the structure of LSTM cell in LSTM neural network, and the structure of DL-based CSK-SS UWA communication system are introduced. In Section 3, a detailed description of the environment configuration and parameter settings in the simulation and the simulation results are given. In Section 4, we provide a water tank experiment and data analysis, and share some suggestions for future sea trials. Section 5 summarizes this paper and gives prospects for the future.
# NOVA Mobility Assistive System: Developed and Remotely Controlled with IOPT-Tools
## 3 Related Work
CVIS core technology is CALM (Communications Air-interface, Long and Medium Range) (ISO TC204 WG16) [63]), which provides V2V (Vehicle to Vehicle), V2I (Vehicle to Infrastructure), and I2I (Infrastructure to Infrastructure) communications. COOPERS project purpose was the development of new safety services based on a two-way communication between infrastructure elements and vehicles. Finally, SAFESPOT project cooperated with CVIS and COOPERS projects and had complementary objectives. All of these works use wireless technologies to support communication between the road elements. Infrastructureelements are often used as service providers and vehicles as consumers, except in the CVIS project, where these roles are not defined. This topic has been studied and funded since a few years ago, but it is still a very current topic with high interest from the scientific community, as evidenced by the recent journal papers [64; 65; 66] and new versions of the ITS-G5 standard [67] produced by ETSI (European Telecommunications Standards Institute) Technical Committee ITS. CVIS, COOPERS, and SAFESPOT projects took place about 10 years ago; however, many scientific contributions have been made since. Model-driven development approaches have been proposed to support intelligent transport systems, mainly their simulation and verification, such as in [68] and [69]. The model-driven development of simulations for intelligent transport systems is proposed in [68], where a framework with guidelines and tools is proposed to specify and simulate these systems. ITS are specified while using a modeling language, which are then transformed into simulation models that support the simulation code generation. With this approach, it is possible to avoid mismatches between the system model and its simulation code, which may exist when these tasks are manually performed. A model-driven verification and validation approach, for computed-based control systems, was presented in [69] and applied to railway signaling. Model-driven development approaches have also been used for implementation purposes, such as in [70], where a Model-Driven Architecture (MDA) approach was used. To conclude this section, the proposed mobility assistive system (NOVA-MAS) and its development approach are briefly compared with the related work. The NOVA-MAS is a complementary system to crowdsourcing applications and smart wheelchairs and may be integrated with them. The authors of this paper do not know any similar work that promotes the propagation of information on road infrastructures and vehicles, in order to make the routes of wheelchair users safer, considering other individuals and vehicles on the public road; or any similar development approach, applied to connected and dynamic road infrastructures. The proposed model-driven development approach simultaneously supports the specification, simulation, model-checking, implementation, and remote control and monitoring, through automatic code generation.
## 5 Conclusions  
This study investigated the impact of metaphorical virtual classrooms and interactive learning objects on student interaction in online mode. For this purpose, the latest version of Moodle was implemented at the University of Otavalo, along with gamification plugins and interactive tools. The methodology included data collection using ordinal instruments for teachers and performance metrics for students, collected through a plugin developed to perform direct queries to the Moodle database for each student, which obtained the average metrics for each virtual classroom of the previous system and the new system implemented. This information was statistically processed using Mahalanobis distances, Confirmatory Factor Analysis, and the Wilcoxon Signed-Rank test to contrast the previous system with the newly implemented system, which allowed significant improvements to be identified in each metric and factor considered.  
The findings evidenced significant increases in students' academic performance, interaction, progress, and time spent learning in virtual environments. Implementing metaphorical virtual classrooms and integrating interactive and gamification tools proved to be effective strategies for improving student motivation and engagement in online learning environments. Regarding the teachers, we evaluated their perception after using the new system, where they rated the new system as significantly easier to use Moodle, create educational resources, create interactive learning objects, and integrate artificial intelligence for designing their content and courses, which clearly suggests that the implementation of the latest educational technologies implemented from an interactive perspective represents a tool that makes teachers' work easier.  
Thus, this study contributes to the field of online education by providing empirical evidence on the effectiveness of implementing metaphorical virtual classrooms and interactive learning objects to improve student interaction and achievement. From the results, it can be concluded that the adoption of advanced educational technologies and innovative pedagogical strategies is essential to addressing the challenges of attrition and motivation in online education.  
Conceptualization, J.I.M.-O.; Methodology, E.P.H.-G.; Software, E.P.H.-G.; Formal analysis, E.P.H.-G.; Investigation, E.P.H.-G.; Writing--original draft, E.P.H.-G.; Writing--review & editing, J.I.M.-O.; Supervision, J.G.L.-B. and J.I.M.-O.; Project administration, J.I.M.-O. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the State Polytechnic University of Carchi (www.upec.edu.ec).  
Not applicable.  
Data Availability StatementWe provide all data gathered for experimental evaluation and the developed Moodle plugin as supplementary material in the GitHub repository for reproducibility: [[https://github.com/erickherrerearesearch/MoodleMonitoring](https://github.com/erickherrerearesearch/MoodleMonitoring)]([https://github.com/erickherrerearesearch/MoodleMonitoring](https://github.com/erickherrerearesearch/MoodleMonitoring)), accessed on 27 March 2024.
## 3 Hand Orthosis Development
### Design Requirements
#### 3.2.1 Engineer-Specific  
When designing hand orthoses, it is important to find a balance between robustness and weight. The orthosis must withstand the wear and tear of daily use, ensuring long-term reliability and reducing the need for frequent replacements. At the same time, it should remain as light as possible, to prevent user fatigue and discomfort during prolonged use. Employing **lightweight** and **durable materials**, like advanced polymers and metals, helps to maintain the orthosis's structural integrity over time and provide consistent support to the user. Furthermore, this also enables a more **minimalistic design**, which avoids interference with the ADL, allowing the user to perform tasks without unnecessary hindrance. This can be achieved by designing the orthosis to cover only essential areas or by utilizing lattice structures [29]. For optimal comfort, the maximum recommended weight for hand orthoses is 200 g [30], with commonly used materials typically having a thickness of up to 3.2 mm.  
Designers must consider **technological limitations**, to ensure that the design is feasible within current manufacturing capabilities and utilizes practical processes. This includes considering the technologies available for creating the orthosis and ensuring that the design can be produced at a reasonable cost and time. This consideration helps in the practical implementation and scaling of the design. This practicality is also important for making the orthosis widely **accessible**, considering global variations in resources and manufacturing infrastructure, to ensure affordability for patients. Balancing the cost with the quality of materials, design, and technological processes is important for making the orthosis accessible to a broader group.  
The orthosis should be designed for **sustainability**, focusing on reuse, adjustability, and recyclability [31]. Incorporating green manufacturing techniques, modular designs, and adjustable components, as well as enabling repairs or modifications without the need for full device replacement, minimizes waste and the environmental footprint [31; 32]. Materials should also be selected considering recyclability, ensuring the device can be effectively managed at the end of its life.
## 3 Method
### Crop Mapping  
Due to the spectral characteristics of different vegetation are very similar, distinguishing different types of vegetation using multispectral images is quite difficult. However, the crop calendars of the main crops in Bole and Luntai are different (Table 3), allowing us to take advantage of crop phenology information to map crops. Crops in Bole and Luntai were mapped using the phenology information by three steps. First, the vegetation area was extracted using the threshold method. In time series NDVI data, pixels with NDVI greater than 0.2 for a month were classified as vegetation. Other pixels were classified as non-vegetation. Then, the planting patterns for all pixels were extracted according to the number of peaks in the time series NDVI data. According to the ecosystem rules, span between peaks for forest, shrubland or grassland and crops should be longer than four months, two months, and 1.5 months, respectively [45], and the land cover types in Luntai and Bole are crops and forest. Thus, pixels with two successive peaks (the time between two peaks being longer than one and a half months) were classified as wheat-corn while the planting patterns of other pixels were set to one crop. Finally, pixels with one-crop planting patterns were classified as tree, cotton, and summer corn, using the maximum likelihood method with two thirds of the field survey data as ROIs for OGI and OGD data.