esa-sceva/satcom-chunk-collection huggingface dataset:
# Management Platforms and Protocols for Internet of Things: A Survey
## 7 IoT Device Management Protocols
### COntrained Networks and Devices MANagement (COMAN)
#### 7.1.1 CoAP--COntrained Networks and Devices MANagement  
CoAP is an easy to use protocol intended for devices with constrained resources and in conformation with the REST Style. It is a specialized Web transfer protocol designed for M2M applications. It was developed to be used along with lower-level protocols and has been used in many IoT candidates along with IPv6 and UDP.  
Also, this protocol meets most requirements for COMAN, such as group-based provisioning, capability discovery, support for energy optimized protocols, unreachable devices and lossy links [66; 67].  
As shown in Figure 16, the CoAP architecture abstracts all network elements as resources, called Universal Resource Identifier (URI) [68]. Inside CoAP management features, it can detect, with low complexity, if a device is online with a simple CoAP ping and verify if the server is stateless.  
Also, in the fog computing architecture [7], it is possible to see the performance of this protocol compared to NETCONF and SNMP. This protocol can be used along DTLS (Data- gram Transport Layer Security) [69].  
_Pros: Standard communication model and secure._  
_Cons: No supports the heterogeneity networks._  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Technology** & **Description** \\ \hline \multirow{3}{*}{CoAP} & The IETF has defined a binary protocol, the Constrained \\  & Application Protocol (CoAP), easy to analyze and especially designed for \\  & constrained devices, which is used with lower-level protocols, but it is \\  & particularly adapted over UDP/IPv6. \\ \hline \multirow{3}{*}{OMA-LwM2M} & OMA Lightweight M2M is a Device Management protocol used \\  & to M2M networks environment. \\ \hline \multirow{3}{*}{OMA-DM} & OMA Device Management provides functions for device \\  & management. The Device Management happens through communication \\ \cline{1-1}  & between a server (Device Manager) and the client (Device Agent) \\ \cline{1-1}  & using HTTP transport. \\ \hline \hline \end{tabular}
\end{table}
Table 3: COMAN—Candidate Technologies.
## 3 Results and Discussion
### Process Water (PW)--Ecotoxicity and Characterization  
Acute toxicity tests with PW-180, PW-215, and PW-250 were carried out on the micro-crustacean _Daphnia magna_ following OECD guideline 202 (2004) (Section 2.4.1). Exposure of _D. magna_ to the PW-180, PW-215, and PW-250 showed high toxicity, with inhibitory effects observed after 48 h of exposure at the lowest percentage for all the PWs tested. The effect was enhanced by increasing the PW concentration in the medium (Figure 6). PWs can be considered as complex mixtures of dissolved organic compounds and nutrients (Tables 5 and 6). The CODs of PW-180, PW-215, and PW-250 were 12.87 \(\pm\) 0.55, 12.22 \(\pm\) 0.35, and 17.33 \(\pm\) 0.75 g\(\cdot\)L\({}^{-1}\)[12]. Regarding total nitrogen, the values for PW-180, PW-215, PW-250 were 1.02 \(\pm\) 0.09, 0.92 \(\pm\) 0.06, and 1.00 \(\pm\) 0.11 g\(\cdot\)L\({}^{-1}\), respectively. Both parameters align with other PWs reported in the literature, as presented in Table 6.  
Figure 5: Removal percentage of methylene blue adsorption after five cycles by hydrochar (H-180) using an initial dye concentration of 100 mg\(\cdot\)L\({}^{-1}\) and a hydrochar load of 3 g\(\cdot\)L\({}^{-1}\) at pH 10, 30 \({}^{\circ}\)C, and 100 rpm for 16 h.  
Figure 6: Average number of mobile _Daphnia magna_ microcrustaceans (bars \(\pm\) standard deviation, n = 6) after 48 h of exposure to process water (PW) from co-hydrothermal carbonization (Co-HTC) of sawdust and non-dewatered sewage sludge at 180, 215, and 250 \({}^{\circ}\)C. Asterisks (*) represent a significant increase in the number of immobile microcrustaceans compared with the respective control (Dunnett’s test, \(p\leq\) 0.05). The presence and interaction of PW compounds in the exposure medium probably resulted in the toxic effects observed for _D. magna_[62; 63]. [PERSON] and colleagues showed the high toxicity of PW from Co-HTC of vegetable oil industry waste and sewage sludge to _D. magna_ (EC\({}_{50}\) = 0.5-2%) [64]. In another study, the PW from HTC of microalgae was toxic to _Allivibrio fischeri_ (EC\({}_{50}\) = 1.8%) [65]. For _Lenna minor_, the PW from sewage sludge was also harmful, causing complete decay at a 10% dilution [66]. In all the studies mentioned, the justification for the effects observed is consistent with our findings, which are also related to the complexity of PW composition (Tables 7 and 8). \begin{table}
\begin{tabular}{c c c c c} \hline  
When comparing the toxicities of PWs from co-HTC at different temperatures, the EC\({}_{50}\) values indicated the highest toxicity for PW-250 \(>\) PW-215 \(>\) PW-180, with values of 0.51% (0.48-0.54%), 0.97% (0.95-1.00%), and 1.13% (1.09-1.17%), respectively. These results suggest that the increase in Co-HTC temperature elevated the toxicity on _D. magna_. The observed increase in toxicity aligns with the rise in compound generation due to the temperature increase (Table 8). A possible explanation for this behavior could be the high level of acetate present in the PWs (Table 7). As lignocellulosic biomass, sawdust is composed mainly of cellulose, hemicellulose, and lignin [67]. During hydrothermal
## 4 Dynamic Tolerance Allocation Based on As-Built Data  
### Dynamic Tolerance Allocation Flow among Assembly Processes  
The LSDM's pointing angle \(\theta\) in space is an index on the service performance. According to the assembly error model built in the previous section, the factors that affect the pointing accuracy include the positioning error, hinge clearance, and truss rod deformation. The hinge clearance is determined by the parts' manufacturing accuracy. In the assembly stage, the accurate fit clearance can be obtained by measuring the size of the hole and shaft. The rod deformation can be calculated by the rod length and the angle between the rod and the horizontal plane. Therefore, the tolerance allocation refers to the allocation of the positioning accuracy tolerance for each hinge.  
The above sections provide the assembly error propagation model for improving the LSDM's service performance. Additionally, each assembly process' tolerance can be divided according to the error propagation model. In the traditional assembly error mode, the tolerance allocation scheme is allocated before assembly, and it usually remains unchanged during the entire assembly process. However, this mode ignores the usefulness of the as-built data, which is uneconomical for assembly.  
In this paper, a dynamic allocation method of assembly tolerance based on the as-built data is proposed. The tolerance dynamic allocation flow is shown in Figure 11. Before the assembly task starts, the process planner provides an initial tolerance allocation solution that can meet the product performance requirements based on experience. During the assembly process, the components corresponding to the operation will determine an actual error value within the design tolerance. Based on the completed process' actual error value, which is called the as-built data, the dynamic allocation of the subsequent tolerance is realized by the GA. Generally, the as-built data are not the boundary value of the tolerance, so subsequent tolerances can usually be expanded to reduce the assembly difficulty and costs. However, when the as-built data are close to the tolerance boundaries or occasionally exceed the tolerance, this method ensures the final assembly quality by reducing the tolerances in subsequent processes in time.  
Figure 11: Dynamic allocation of tolerance among assembly processes.
## 1 Introduction
More specifically, this paper improves the adaptability of MACC-based adaptive filtering by working out a generalized form of the algorithm. The adjustment of the shape parameter can balance the steady-state performance and convergence rate of the GMACC algorithm. In practical data of regression analysis or adaptive filtering, there are noises distributed with asymmetric heavy tails extending out towards positive or negative values. For example, [PERSON]. [23] applied a robust regression in automobile insurance premium estimation that figured out the risk of a driver given a profile (age, type of car, etc. ), and revealed the asymmetric heavy-tail noise problem that the premium had to take into account the tiny fraction of well-behaved drivers who cause serious accidents and large claim amounts. Moreover, the asymmetric heavy-tail noise problem could not be neglected in time series analysis such as oil-price-related stock analysis [24]. This paper studies robust adaptive filtering based on GMACC and applies it to network delay prediction. As far as the authors know, although the network delay prediction is very important in remote tasks such as space telemetry [32] and satellite link handover management [33], the asymmetric property of the network delay, especially of the queue delay, has not been discovered and described so far. The main contributions of this paper are as follows: (1) The GMACC is obtained by the expansion of MACC, and the relationship of different robust criteria is discussed. GMACC-based robust adaptive filtering is proposed and its properties are analyzed. (2) The steady-state performance of GMACC-based robust adaptive filtering is analyzed theoretically and verified by simulation experiments. (3) The asymmetric property of the satellite network delay is discovered and described. (4) Simulations verify the effectiveness of the GMACC-based adaptive filter in satellite network delay prediction.
# Automated Visual Identification of Foliage Chlorosis in Lettuce Grown in Aquaponic Systems
## 5 Conclusions  
This study discusses the major problem of lettuce foliage chlorosis in an aquaponics context. The 'HSV Color Segmentation' image processing approach was used to segment the lettuce images obtained from various resources. The segmented images were divided into two classes, 'Green Foliage-No Leaf Chlorosis' and 'Yellow Foliage-Leaf Chlorosis'. Then, the foliage color detection model was developed, and a quality indicator was defined to identify leaf chlorosis and determine the quality of the lettuce crop. The model is validated, achieving an overall accuracy of 95%. The performance of the model was also compared with existing similar methods. The results show that the proposed method has outperformed these existing methods. A cloud-based application was then developed, where the final model was deployed. The ontology model that contains knowledge related to the causes of lettuce crop chlorosis was also integrated with the final model. The proposed system proves to be accurate and flexible enough to be used in real scenarios and, hence, is not limited to being disturbed by potentially changing conditions and environments.  
For future work, the system will be extended to include other crops. Moreover, images with complex backgrounds and multiple objects will also be added to the dataset. The ontology model will also be extended to include the specific treatments for potential causes of leaf chlorosis.  
Conceptualization, R.A. ([PERSON]), P.M. and R.A. ([PERSON]); methodology, R.A. ([PERSON]) and P.M.; validation, R.A. ([PERSON]); investigation, R.A. ([PERSON]); writing--original draft, R.A. ([PERSON]); writing--review and editing, P.M. and R.A. ([PERSON]); supervision, P.M. and R.A. ([PERSON]); project administration, R.A. ([PERSON]); funding acquisition, P.M. and R.A. ([PERSON]). All authors have read and agreed to the published version of the manuscript.  
The authors acknowledge the financial support of this work from the Natural Sciences and Engineering Research Council of Canada (NSERC) (Grants File No. ALLRP 545537-19 and RGPIN-2017-04516).  
The authors declare no conflict of interest.
# ADPSCAN: Structural Graph Clustering with Adaptive Density Peak Selection and Noise Re-Clustering
## 4 Method  
In this section, we propose a structural graph clustering algorithm named ADPSCAN, which includes adaptive density peak selection and noise re-clustering parts. Our algorithm aims to address the parameter dependency issues inherent in traditional SCAN algorithms, significantly enhancing clustering accuracy. Traditional SCAN algorithms typically rely on manually setting parameters \(\epsilon\) and \(\mu\). To overcome this challenge, we propose analyzing data trends in decision graphs and utilizing the generalized extreme value distribution to automatically select thresholds for local density and dependency similarity,thereby further enabling the selection of density peak nodes. This automated approach identifies density peaks as potential clustering centers, reducing the manual intervention required and making the clustering process more automated. Additionally, we propose distance-based structural similarity to effectively handle noise nodes, accurately reassigning these nodes to appropriate clusters based on their structural similarities with clusters. This further enhances the algorithm's accuracy. Framework of our algorithm is shown in Figure 2. We will now provide a detailed description of each component.  
Figure 1: Visualization of Key Definitions in the Problem Statement.
# Utilization of By-Products from the Fruit and Vegetable Processing Industry in Pasta Production
## 3 Incorporation of By-Products
### Antimicrobial Activity  
It is known that many fruit and vegetable by-products, especially their extracts, have some antimicrobial activity, particularly against pathogenic bacteria, which is linked to the presence of certain components [115]. In fact, this characteristic has been used for their reintroduction into the food chain to extend the shelf life of various food products [116]. In most cases, pasta is a product that is sold with low moisture and low water activity, meaning that microbial growth does not usually pose a problem for its preservation. However, fresh pasta is also commercially available. This type of pasta, with high water activity, is produced in specialized facilities under appropriate temperature control and must be stored under refrigeration to extend its shelf life, often being packaged in modified atmospheres. In this case, it is beneficial to minimize microbial growth.  
Studies on the antimicrobial activity of some by-products and the effect of their inclusion in pasta formulations to extend shelf life have focused on fresh pasta. Positive results have been found with mixtures of broccoli by-products with olive oil pomace and pomeranate peels [78], fig peels [47], cucumber pomace [84], grape pomace [64], and an extract of phenolic compounds from artichoke by-products [76]. In some of these studies, a slight but statistically significant increase in acidity [84] or a decrease in pH [47; 78] has been observed. These modifications could help reduce microbial growth and thus increase the shelf life of the pasta, but they do not fully explain the observed effect, which is generally stronger against bacteria than against molds and yeasts. This effect could be attributed to some antimicrobial component, as it is known that such compounds exist in fruits and vegetables. However, these have not been identified or quantified in the studies conducted.
## 2 Material and Methods
### Experimental Diets  
Experimental diets had different EO-OG inclusion levels: 0.0, 1.0, 2.0, and 3.0 g kg\({}^{-1}\) (Table 1). The chosen dietary levels were based on previous similar studies and former studies of our research group [11; 24; 40; 41]. These studies show that these inclusion levels are recommended to achieve potential beneficial effects (e.g., antioxidant effect). Additionally, due to the under-researched biotoxicity of EO-OG on _M. rosenbergii_, this study adopted a conservative approach by testing small initial inclusion levels within a small range.  
Diets were formulated to have a 30% crude protein inclusion level, using SuperCrac(r) 2.0 software and following the recommendations of the NRC [42]. For feed preparation, ingredients were graded (0.8 mm particle size) and sieved (250 \(\upmu\)m mesh). Subsequently, ingredients were dosed according to the respective diet formulation and mixed for processing. Feed pellets were then moistened with water (35 \({}^{\circ}\)C), extruded into 1 mm diameter pellets, and dried at 45 \({}^{\circ}\)C for 24 h. Final feed pellets were stored at 4 \({}^{\circ}\)C until further use.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Ingredients (g kg\({}^{-1}\))**} & \multicolumn{4}{c}{**Experimental Groups (g kg Diet\({}^{-1}\))**} \\  & **Control** & **1.0** & **2.0** & **3.0** \\ \hline Soybean meal & 400.00 & 400.00 & 400.00 & 400.00 \\ Wheat bran & 98.10 & 98.10 & 98.10 & 98.10 \\ Wheat flour & 154.65 & 154.65 & 154.65 & 154.65 \\ Fish meal & 150.00 & 150.00 & 150.00 & 150.00 \\ Offal meal & 92.50 & 92.50 & 92.50 & 92.50 \\ Fish oil & 42.40 & 41.40 & 40.40 & 39.40 \\ Soy lecithin & 20.00 & 20.00 & 20.00 & 20.00 \\ Limestone & 15.65 & 15.65 & 15.65 & 15.65 \\ Salt & 8.00 & 8.00 & 8.00 & 8.00 \\ Vitamin and mineral premix \({}^{\ddagger}\) & 8.00 & 8.00 & 8.00 & 8.00 \\ Corn starch & 5.00 & 5.00 & 5.00 & 5.00 \\ DL-methionine & 2.90 & 2.90 & 2.90 & 2.90 \\ L-lysine & 1.60 & 1.60 & 1.60 & 1.60 \\ Antifungal & 1.00 & 1.00 & 1.00 & 1.00 \\ Butylated hydroxytlouene & 0.20 & 0.20 & 0.20 & 0.20 \\ EO-OG & 0.00 & 1.00 & 2.00 & 3.00 \\ Total & 1000.00 & 1000.00 & 1000.00 & 1000.00 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Feed formulation and nutrient analysis of the experimental diets with different _Oximum gratissimum_ essential oil inclusion levels for _Macrobrachium rosenbergii_ juveniles.
# Understanding and Classifying Permanent Denial-of-Service Attacks
## 3 Case Studies of PDoS Attacks
### VPNFilter  
VPNFilter, detected in 2018, is a multi-stage malware targeting routers and storage devices, including Linksys, MikroTik, Netgear, TP-Link, and QNAP. It includes a module, dstr, that renders infected devices inoperable. The dstr module, once executed, deletes files necessary for normal operation, including those associated with the malware itself, likely to obscure its presence during forensic analysis. It targets running processes related to VPNFilter and others for termination and then deletes various system files and directories. Significantly, it overwrites the bytes of all available /dev/mtdX devices with a 0 xFF byte, erasing the flash memory. Finally, it executes a command to delete the remaining file system and reboots the device, leaving it unable to operate normally.
# Inverse Properties in Neutrosophic Triplet Loop and Their Application to Cryptography
###### Abstract  
This paper is the first study of the neutrosophic triplet loop (NTL) which was originally introduced by [PERSON]. NTL originated from the neutrosophic triplet set \(X\): a collection of triplets \((x,neut(x),anti(x))\) for an \(x\in X\) which obeys some axioms (existence of neutral(s) and opposite(s)). NTL can be informally said to be a neutrosophic triplet group that is not associative. That is, a neutrosophic triplet group is an NTL that is associative. In this study, NTL with inverse properties such as: right inverse property (RIP), left inverse property (LIP), right cross inverse property (RCIP), left cross inverse property (LCIP), right weak inverse property (RWIP), left weak inverse property (LWIP), automorphic inverse property (AIP), and anti-automorphic inverse property are introduced and studied. The research was carried out with the following assumptions: the inverse property (IP) is the RIP and LIP, cross inverse property (CIP) is the RCIP and LCIP, weak inverse property (WIP) is the RWIP and LWIP. The algebraic properties of neutrality and opposite in the aforementioned inverse property NTLs were investigated, and they were found to share some properties with the neutrosophic triplet group. The following were established: (1) In a CIPNTL (IPNTL), RIP (RCIP) and LIP (LCIP) were equivalent; (2) In an RIPNTL (LIPNTL), the CIP was equivalent to commutativity; (3) In a commutative NTL, the RIP, LIP, RCIP, and LCIP were found to be equivalent; (4) In an NTL, IP implied anti-automorphic inverse property and WIP, RCIP implied AIP and RWIP, while LCIP implied AIP and LWIP; (5) An NTL has the IP (CIP) if and only if it has the WIP and anti-automorphic inverse property (AIP); (6) A CIPNTL or an IPNTL was a quasigroup; (7) An LWIPNTL (RWIPNTL) was a left (right) quasigroup. The algebraic behaviours of an element, its neutral and opposite in the associator and commutator of a CIPNTL or an IPNTL were investigated. It was shown that \((\mathbb{Z}_{p},*)\) where \(x*y=(p-1)(x+y)\), for any prime \(p\), is a non-associative commutative CIPNTL and IPNTL. The application of some of these varieties of inverse property NTLs to cryptography is discussed.  
neutrosophic; triplet loop; quasigroup; loop; generalized group; neutrosophic triplet group; group; cryptography +
Footnote †: journal:
###### Abstract  
In the process of mining, a large area of hard roof will be exposed above a goal and may suddenly break. This can easily induce rock burst and has a significant impact on production safety. In this study, based on the engineering background of the hard roof of the 2102 working face in the Balasu coal mine, the spatial and temporal characteristics of the strain energy of the roof during the initial mining process were explored in depth. Based on a theoretical calculation, it is proposed that hydraulic fracturing should be carried out in the medium-grained sandstone layer that is 4.8-22.43 m above the roof, and that the effective fracturing section in the horizontal direction should be within 30.8 m of the cutting hole of the working face. The elastic strain energy fish model was established in FLAC(tm) to analyze the strain energy accumulation of the roof during the initial mining process. The simulation and elastic strain energy results show that, as the working face advances to 70-80 m, the hard roof undergoes significant bending deformation. The energy gradient increases with the rapid accumulation of strain energy to a peak value of 140.54 kJ/m3. If the first weighting occurs at this moment in time, the sudden fracture of the roof will be accompanied by the release of elastic energy, which will induce rock burst. Therefore, it is necessary to implement roof cutting and pressure relief before reaching the critical step of 77 m. To this end, the comprehensive hydraulic fracturing technology of 'conventional short drilling + directional long drilling' is proposed. A field test shows that the hydraulic fracturing technology effectively weakens the integrity of the rock layer. The first weighting interval is 55 m, and it continues until the end of the pressure at the 70 m position. The roof collapses well, and the mining safety is improved. This study provides an important reference for hard roof control.  
hard roof; first weighting; strain energy; hydraulic fracturing roof cutting; roof collapse +
Footnote †: journal: Medical Engineering  
1 State Key Laboratory for Fine Exploration and Intelligent Development of Coal Resources, School of Mines, China University of Mining and Technology, Xuzhou 221116, China 1  
Key Laboratory of Mining Coal Resources Green Mining, Xinjiang Key Laboratory of Coal-Bearing Resources Exploration and Exploitation, Xinjiang Engineering Research Center of Green Intelligent Coal Mining, Xinjiang Institute of Engineering, Urumqi830023, China 3  
College of Mining Engineering, Taiyuan University of Technology, Taiyuan 030024, China 3