esa-sceva/satcom-chunk-collection huggingface dataset:
# A Survey of Handwritten Character Recognition with MNIST and EMNIST
## 4 Conclusions

Table 3: Side-by-side comparison of the results for the EMNIST dataset, including works using similar datasets from NIST Special Database 19. Best results are boldfaced. Results marked with a star (*) indicate that they refer to works using samples from NIST SD 19 which are similar but not equivalent to EMNIST (samples are the same, but they are not submitted to the preprocessing stage used in EMNIST, described in the text). algorithms or other optimization techniques in order to enhance the selection of hyperparameters, leading to better accuracy. In other cases, different CNN models are combined into a committee, reducing classification error. Also, from the surveyed works we can infer that data augmentation techniques can enhance performance. These techniques are most often used with neural networks or SVMs, and when combined with a CNN classifier they are able to make the top of the absolute ranking in the MNIST dataset. As a general conclusion, we can see how during two decades, there has been no significant changes in the artificial intelligence techniques used for computer vision. Indeed, most of the merit of the good performance can be attributed instead to hardware improvements, which has eventually led to more complex architectures and the ability to deal with higher amounts of data. Still, some works are proposing novel developments or improvements, which are often combined with convolutional neural networks, reporting outstanding results. Although accuracy in MNIST and EMNIST is very close to 100% and will hardly increase, these novel developments might hold the key for breaking more complex computer vision problems. Conceptualization, A.B., Y.S. and P.I. ; methodology, A.B. and Y.S. ; investigation, A.B. and Y.S. ; writing-original draft preparation, A.B. ; writing-review and editing, A.B, Y.S. and P.I. ; supervision, Y.S. and P.I. ; funding acquisition, A.B. and Y.S. This research was partially funded by Ministerio de Educacion, Cultura y Deporte under FPU fellowship with grant number FPU13/03917. The authors declare no conflict of interest. The following abbreviations are used in this manuscript: \begin{tabular}{l l} BFGS & Broyden-Fletcher-Goldfarb-Shanno algorithm \\ CG & Conjugate gradient \\ C-SVDD & Centering support vector data description \\ CNN & Convolutional neural network \\ COSFIRE & Combination of shifted filter responses \\ DCT & Discrete cosine transform \\ DWT & Discrete wavelet transform \\ ELM & Extreme learning machine \\ EMNIST & Extended MNIST \\ K-NN & \(k\)-nearest neighbors \\ MNIST & Mixed National Institute of Standards and Technology \\ NN & Neural network \\ PCA & Principal component analysis \\ RNN & Recurrent neural network \\ SIFT & Scale-invariant feature transform \\ SVM & Support vector machine \\ \end{tabular}
## 1 Introduction
The authors of [9] introduced a transmission line insulator fault diagnosis method based on the binary support vector machine classifier and Bayesian optimization, which was used for the classification and recognition of the infrared spectrum in the process of insulator flashover. The authors of [10] selected six components of reciprocating compressors from an infrared image, and the average grayscale values were calculated to form 6-dimension vectors to represent the temperature distribution. Then, SVM was sued to diagnose the faults, with more than a 99% classification accuracy. According to the existing research works, state identification using infrared image features has mostly been used in long-distance monitoring or static detection while applications for near-field online detection are rare. Fault identification using infrared image features can reflect the temperature distribution and further identify the conductive states of copper rods, which is feasible for the detection of the conductive state of copper rods based on infrared images. Therefore, in this paper, this method is applied to identify the conductive state of copper rods with near-field online detection. A nickel electrolysis workshop contains a large number of nickel electrolytic cells. Cathode and anode copper rods are placed alternately and equidistantly, which suspend cathode and anode nickel plate, respectively, by hangers. The diameters of cathode and anode copper rods are 35 and 45 mm, respectively. Both sides of the electrolytic cell have insulated partitions and busbars. In the traditional manual detection procedure, workers need to detect the conductive state of copper rods periodically by touching the copper rods and observing sparks in the instantaneous short circuit between cathode and anode copper rods. Figure 1 shows the nickel electrolytic cells and the conventional manual detection. The conventional manual method has many disadvantages, such as low efficiency, heavy workload, high labor intensity, insulating safety, and missed detection.
# CoAR: Congestion-Aware Routing Protocol for Low Power and Lossy Networks for IoT Applications
## 3 The RPL and Problem Description
### Communication Models  
RPL supports three types of communication patterns that are point-to-point (P2P), point-to-multipoint (P2 MP) and multipoint-to-point (MP2P). P2P is the routing between any two nodes in the DODAG. P2 MP is the downward traffic transmitted from the root to the multiple nodes. On the other hand, MP2P is related to data collection traffic forwarded from child nodes towards the root node which is the main traffic flow in most of the IoT applications. The destinations of MP2P traffic is mainly DODAG root.
###### Abstract  
Graphene platelets (GPLs) can be used to enhance the mechanical and electrical properties of the matrix material, which efficiently determines and improves the dynamic behavior in composite structures. Based on the first-order shear deformation theory, this paper investigates the vibration and wave problems in a functionally graded graphene-reinforced composite plate. The composite plate is composed of the polymer matrix reinforced with GPLs that are dispersed along the thickness direction, following four kinds of functionally graded patterns. The governing equation of dynamic problems in the composite plate can be described in the state space formulation, and be solved using the method of reverberation-ray matrix (MRRM). Unlike the traditional state space method, this method is unconditionally stable due to introducing the dual coordinates, which can inherently avoid the numerical instability. After a validation study to verify the present analysis, a parametric study is conducted to analyze the effect of weight fraction, size and distribution patterns of the reinformers, as well as the boundary conditions and aspect ratios on the dynamic behaviors of the composite plate, hence providing a better way to achieve improved dynamic resistances of the GPLs composite plates.  
graphene platelet; functionally graded composite plate; free vibration; wave propagation; the method of reverberation-ray matrix +
Footnote †: journal: Applied Sciences
## 5 Discussion and Conclusions
In the second situation, the production of electricity takes the following values: 20 MWh, 23 MWh, 20 MWh, 10 MWh, and 25 MWh. In these situations, despite the differences in electricity production and the price of electricity, the CRS parameter comes out the same. However, the CPS parameter is different. Therefore, it is necessary to consider both parameters and not just the CRS. Based on the conducted research, the next step is to investigate similar impacts of other energy sources in different countries; for example, in Germany, analysis could focus on wind energy, whereas in Slovakia it might concentrate on hydro energy or other energy sources. The research described in this paper should be applicable to any energy source. By comparing the results, the study highlights the specific impacts of various sources of electrical energy in individual countries. Consequently, it is possible to focus on the production from these energy sources when predicting electricity prices in a given country. Conceptualization, M.P. ; methodology, M.B. ; software, M.P. ; validation, M.P. and M.B. ; formal analysis, M.P. and M.B. ; investigation, M.P. and F.K. ; resources, M.B. ; data curation, M.P. and M.B. ; writing, M.P., M.B. and F.K. ; visualization, M.B. ; supervision, M.P. ; project administration, M.P. ; funding acquisition, M.P. All authors have read and agreed to the published version of the manuscript. This work was supported by the Slovak Research and Development Agency under the contract no. APVV-19-0576 and the Ministry of Education, Science, Research and Sport of the Slovak Republic and the Slovak Academy of Sciences under the contract no. VEGA 1/0757/21. Not applicable. The data presented in this study are available on request from the corresponding author. The data in this paper are publicly unavailable due to privacy restrictions. All support for this paper is covered by the author contribution or funding sections. The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline Produce in MWh & 25 & 23 & 20 & 10 & 25 \\ \hline Price in \(\mathbf{\ell}\)/MWh & 2.5 & 5 & 4 & 4 & 8 \\ \hline CPS & 4.830097 & & & & \\ CRS & 102.77\% & & & & \\ \hline Produce in MWh & 20 & 23 & 20 & 10 & 25 \\ \hline Price in \(\mathbf{\ell}\)/MWh & 15 & 20 & 10 & 12 & 14 \\ \hline CPS & 14.59184 & & & & \\ CRS & 102.76\% & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparison of two situations with different electricity production values and electricity prices.
# CFD Simulation of the Safety of Unmanned Ship Berthing under the Influence of Various Factors
## 2 Unmanned Ship-Wind and Wave Coupling CFD Model
### Boundary Conditions and Calculation Scheme  
The types of boundary conditions mainly include the velocity inlet (inlet), outlet (outflow), solid wall (wall), water surface (VOF), etc. The established fluid domain, namely the air domain and the water domain, are built in the same module, and there is no need to set the gas-liquid interface [34]. The surface of the ship as a wall and the specific value of the velocity inlet according to different schemes, so that the air velocity was the same as the water flow velocity. The flow outlet is a fully developed flow. We set the hull surface and other outer boundaries as smooth, impenetrable walls with a given roughness. The bottom  
Figure 3: Mid-section mesh after mesh adaptation.  
surface of the water area, due to the relative movement between the riverbed and the hull, it was set as a moving wall, and the other walls were set as non-slip walls.  
The speed of unmanned ships is generally low during berthing: under the condition of no wave interference, set up scheme A and B for the simulation, as described below:  
Option A: the entrance of the calculation domain was set to be about one time the length of the unmanned ship's bow, the exit about three times the length of the ship, the port side was three times the width of the quay wall, the starboard side was one time the width of the quay wall, and the upper part was two times the height of the ship. The lower part was twice the height of the ship [18]. We simulated the safety of berthing at a constant speed when the speed is 0.45, 1, 2, 3, 4, 5, and 5.45 m/s.  
Option B: On the basis of the previous calculation domain, the distance from the right side of the unmanned ship to the shore wall was adjusted to 0.5 times and 1.5 times the width of the ship, to simulate the safety of the unmanned ship's homogenous berthing at speeds of 0.45 m/s and 3 m/s, respectively, and the influence of three different quay wall distances on berthing safety was compared.
# Security in Wireless Sensor Networks: A Cryptography Performance Analysis at MAC Layer
## 5 Performance Evaluation
### BMAC vs. LMAC: Overall Comparison
#### 5.6.1 Bmac and LMAC Comparison Using AEs  
Considering the Figure 15 it is clear that LMAC, generally, is significantly better than BMAC since it is able to guarantee a higher number of received packets and a lesser number of packets that get lost as well as a lesser energy consumption.
## 3 Results
### Catalytic Investigations
#### 3.2.3 Influence of the Noble Metal  
To further investigate the potential of the metal-loaded PSC as tunable catalysts, a variation of the active metal phase used was carried out. For this reason the (13)PSC polymer-silica composite was impregnated with palladium ((1)Pd(13)PSC) and ruthenium ((1)Ru(13)PSC). As it can be seen in Figure 6, the product composition for (1)Pd(13)PSC did not significantly differ from (1)Pt(13)PSC, again indicating a possible limitation of the reaction to \(n\)-octane by the acid-catalyzed ring-opening reaction. This is in agreement with the findings from [PERSON] et al. [17] who also found comparable product compositions in the HDO of FAc for Pt and Pd supported on NbOPO\({}_{4}\) using water as a solvent. Also comparable to their paper, the results using ruthenium as active metal ((1)Ru(13)PSC) differ from the former two. This supports their argument that in the HDO of FAc the active metal may not only act as a hydrogenation catalyst, but also affect the product selectivity due to synergistic effects (e.g., with the support material). The exceptional performance of Ru as a HDO catalyst has also been discussed elsewhere in the recent literature [38; 39] and although the mechanistic details are not fully understood it can be summarized that the product composition in the HDO of FAc can also be tuned via the metal component of the metal/polymer-silica composite catalysts investigated.  
Figure 5: Product fractions obtained for the HDO of FAc carried out using PSC catalysts containing 13 wt.% polymer and different Pt contents (T = 250 \({}^{\circ}\)C, pH\({}_{2}\) = 100 bar, m catalyst = 0.25 g, 0.5 g FAc (24.5 mmol L\({}^{-1}\)) dissolved in 150 mL cyclohexane, stirring speed = 1000 min\({}^{-1}\), X(FAc) \(>\) 99% except for (13)PSC).  
It is furthermore noteworthy comparing the conversion of FAc to \(n\)-octane obtained in this study with the few studies conducted in the literature under similar conditions. The \(n\)-octane product fraction of 0.9 (roughly equaling 90% yield of \(n\)-octane) observed after 8 h of reaction time at 250 \({}^{\circ}\)C and 100 bar H\({}_{2}\) using (1)Ru(13)PSC with a catalyst to reactant mass ratio of 1:2 is comparable to the 94% yield obtained by [PERSON] et al. [30] at 170 \({}^{\circ}\)C, 20 bar H\({}_{2}\), the same catalyst to reactant mass ratio (but a higher noble metal content of 5 wt.%) after 24 h of reaction time using a Pd/Nb\({}_{2}\)O\({}_{5}\)/SiO\({}_{2}\) catalyst. For a more detailed report on the productivity of different bifunctional catalysts in the HDO of FAc, see Table S1.
## 3 Numerical Examples
### 2D-Riemann Problem
#### 3.6.1 Configuration 3  
The initial conditions are  
\[(\rho,u,v,p)=\begin{cases}(1.5,0,0,1.5),&0.8\leq x\leq 1,\ 0.8\leq y\leq 1,\\ (0.5323,1.206,0,0.3),&0\leq x<0.8,\ 0.8\leq y\leq 1,\\ (0.138,1.206,1.206,0.029),&0\leq x<0.8,\ 0\leq y<0.8,\\ (0.5323,0,1.206,0.3),&0.8\leq x\leq 1,\ 0\leq y<0.8.\end{cases} \tag{52}\]  
Generate a uniform grid with a resolution of 400 \(\times\) 400 in the computational domain of [0, 1] \(\times\) [0, 1]. The area is divided into four regions by the two lines x = 0.8 and y = 0.8. All boundaries are non-reflecting boundary conditions. The total simulation time is \(t=0.8\), a fixed time step size of \(DT=1\times 10^{-4}\).  
Figure 14 demonstrates that the solver utilizing the WENO7 scheme provides higher accuracy compared to WENO5, resulting in a more refined and precise flow field resolution. The LF scheme, with its higher dissipation, smooths out the flow field, reducing instability and leading to less detailed results. In contrast, the URLBFS method, characterized by its lower dissipation, is able to resolve a greater number of vortex structures, thus capturing finer flow details.  
Figure 14: Two-dimensionalRiemann problem (configuration 3): Density contours with 31 equally spaced isolines ranging from 0.135 to 1.725 were obtained using the LF, ROE, and URLBFS schemes. The color gradient represents the corresponding density values, with blue indicating the minimum density value. The simulation was conducted at t = 0.8 with a resolution of 400 \(\times\) 400. Panels (**a–c**) show results using the WENO5 reconstruction method with LF, ROE, and URLBFS schemes, respectively. Panels (**d–f**) display corresponding results with the WENO7 reconstruction method.
## 1 Introduction
However, despite the diversity of extraction methods, they are all united by the requirement for meticulous and thorough execution using straightforward, quick, and workable methods that, if possible, are automated [17]. Methodologies can be classified as either conventional or non-conventional, each with its specific advantages and disadvantages [18]. Conventional methods, including soaking, maceration, water percolation, and Soxlet extraction, rely on solvent selection and the use of heat and/or agitation to enhance the solubility of target compounds. Nevertheless, these methods often lead to heat deterioration of compounds due to prolonged extraction times and generally do not adhere to eco-extraction principles [19; 20]. In contrast, numerous novel extraction techniques, such as pressureed liquid extraction, pressurized hot water extraction, ultrasound-assisted extraction, microwave-assisted extraction, supercritical fluid extraction (SFE), and subcritical water extraction (SWE), have been developed and studied [21]. These advanced methods are designed to improve solvent usage, extraction time, quality, and efficiency [22]. Nonetheless, despite the innovative approaches provided by recent technological advances, the efficiency of these extraction methods depends on various factors, including the type of samples and solvents used, as well as the pH, temperature, light, duration of extraction, particle size, solvent/sample ratio, and extraction procedure [17; 23]. The literature indicates that no review has yet been conducted on the methods of extracting bioactive components from _Coriandrum sativum_ (L) or its antioxidant capacity. Therefore, after reporting the outstanding multidisciplinary areas of application of this culinary herb or spice, this work aims to provide a comprehensive review of the conventional and innovative extraction methods of main phytochemical (polyphenols, and crude and essential oils (EO)) from different parts of coriander (_Coriandrum sativum_ L). It is focused on the discussion of the advantages and disadvantages of these processes, while encompassing the set of pretreatments affecting the content of its active compounds. We first document pre-harvest treatments used in the field; then, post-harvest treatments, which refer to the storage period prior to further usage, are documented (Figure 1). This review is intended as a comprehensive reference for researchers and practitioners interested in exploiting the bioactive properties of coriander, highlighting the most effective processes for maximizing its antioxidant potential for possible application in the food and pharmaceutical industries.
# An Adaptive Symmetrical Load Balancing Scheme for Next Generation Wireless Networks
## 5 Results
### Packet Loss Rate  
Figure 8 shows the performance of the packet loss rate. It can be seen that, as there are more WDs, the proposed ASLB, CMAS, and DASA schemes experience a minor increase in packet loss rate, however the MPD and RSSI schemes experience a rapid increase in packet loss rate. Approximately fewer packets are transmitted on average in the ASLB scheme than in the RSSI, MPD, DASA and CMAS schemes. Fewer packets are lost as a result of increased throughput and symmetrical load distribution among the APs and the controller in the ASLB. These outcomes demonstrate the effectiveness of the suggested ASLB for software-defined load balancing among numerous APs. When compared to CMAS, DASA, MPD and RSSI schemes, ASLB reduces the packet loss rate by 25%, 28%, 45% and 56%, respectively.  
Figure 8: Packet Loss Rate Performance.  
Figure 7: Delay Performance.
## 4 Conclusions  
It is feasible to use the \"filter press backwash-chemical precipitation-gaseous membrane absorption\" method for green treatment of cyanide tailings. The main conclusions are summarized as follows:  
1. The main reason for the excessive toxicity of the cyanide tailings was the high concentration of copper-cyanide complexes in the cyanide tailings.
2. The effect of the filter press backwash was mainly affected by air-drying time and backwash water parameters. To decrease the total cyanide concentration in the leached toxic solution of backwashed cyanide tailings to less than 5 mg/L, the primary air-drying time should be 1.5 min; in addition, the secondary air- drying time should be 10 min, the pH value of the backwash water must be greater than 2, the backwash water multiple must be greater than or equal to 0.7, and the total cyanide concentration in the backwash water must be greater than 21.75 mg/L.
3. In the process of chemical treatment, the copper element in the elution water was recovered by acidification and vulcanization. The optimal reaction conditions were as follows: initial pH value of the acidification reaction was 1.8 and NaHS dosage of 100 mg/L. The copper products were composed of CuSCN, CuS, Cu\({}_{2}\)S, and CaSO\({}_{4}\).
4. The effect of gaseous membrane treatment was mainly affected by the flow rate of cyanide-containing water and the number of membrane stages. The best conditions were that the flow rate of cyanide-containing water was 0.3 m\({}^{3}\)/h and the number of membrane stages was two.
5. The process circulation experiment was carried out under optimal conditions to verify the feasibility and stability of the process. In the circulation experiment, the leaching toxicity of the backwashed cyanide tailings reached the TSPC standard for storage in a tailings pond. The average recovery rate of copper and total cyanide in elution water was 97.8% and 99.89%, respectively, and the average removal rate of thiocyanate was 94.09%.  
Conceptualization, J.Y. and S.Y.; methodology, J.Y. and Y.W.; validation, Y.W., P.H. and J.Y.; investigation, J.Y. and X.L.; resources, S.Y. and Y.T; data curation, J.Y.; writing--original draft preparation, J.Y.; writing--review and editing, J.Y. and S.Y.; supervision, P.H.; project administration, Y.W. and X.L.; funding acquisition, S.Y. All authors have read and agreed to the published version of the manuscript.  
We are grateful for the Chinese Academy of Science Project (No. KFJ-STS-QYZD-044) and the National Key R&D Program during the 13 th Five-year Plan Period (2019 YFC1908405) for support of this work.  
Not applicable.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to project requirements.  
Thanks are extended to the Yunnan Gold Group for the support of experimental raw materials.  
The authors declare no conflict of interest.