esa-sceva/satcom-chunk-collection huggingface dataset:
# Study of Orientation Error on Robot End Effector and Volumetric Error of Articulated Robot
## 3 Conclusions  
The following conclusions can be drawn from the investigation on robot accuracy. A new type of kinematic ball link system was designed and tested. This incorporated three points contact between the sockets and the balls and utilized the magnetic force in the socket to locate the link between the reference balls. This new design proved to be successful in operation and provided the following advantages over existing ball bars. This link system is light weight and low cost compare with existing system such as a camera-based system and a laser tracker. Also, the existing system is limited to the measuring area of sensor, and it can measure some working areas when the robot movies in a circle. However, the link system has the advantage of measuring the whole working area of the robot. The accuracy and the repeatability of the link depends mainly on the digital transducer which has a repeatability of 0.5 \(\upmu\)m. The absolute length of the link can be determined precisely by means of a calibrated setting fixture. The performance of the link over the period of the research has shown that it was sufficiently robust for application to robots operating in industrial environments.  
Parametric error components of industrial robots are generally difficult to establish compared with the orthogonal linear axes of machine tools. The research has shown that the techniques devised using basic equipment such as an extended range of ball links, together with a sensitive angular instrument such as a linear transducer, can be successfully applied to establish the orientation and volumetric error. The technique devised using a simulation program for the robot geometry, together with results from a circular test, enables robot errors to be characterized in terms of robot pose error such as roll, pitch, and volumetric characteristics. Circular test data is a valuable technique for characteristic the robot error in terms of robot orientation error and volumetric error etc. The robot orientation error due to robot parametric error. Also, robot pose error was shown a significant factor influencing the accuracy of the robot end effector. Proposed techniques are useful to set up the articulated robot in the industrial site.  
This research was supported by the Tongmyong University Research Grants 2018 (2018A017).  
The authors declare no conflict of interest.
## 3 Results
### Synthesis of the Results  
Reporting of CLAIM Items across the Included Studies  
In all studies, 42 methodological items are reported (Supplementary Table S2). In the abstract section, two studies (33%) did not present a structured summary of the study design, methods, results, and conclusions (item 2) [7; 20].  
In the methods section, no methodological components were reported from the included CNN studies, including the study goal; item 6, model creation, exploratory study, feasibility study, noninferiority trial of study design (n = 6, 100%) [6; 7; 8; 20; 21; 22]; item 7, data source (n = 1, 17%) [20]; item 8, eligibility criteria (n = 3, 50%) [6; 20; 22]; item 9, data-processing steps (n = 1, 17%) [21]; item 11, definitions of data elements, with reference to common data elements (n = 6, 100%) [6; 7; 8; 20; 21; 22]; item 12, de-identification methods (n = 6, 100%) [6; 7; 8; 20; 21; 22]; item 13, how missing data were handled (n = 6, 100%) [6; 7; 8; 20; 21; 22]; item 14, definition of the ground-truth reference standard (n = 6, 100%) [6; 7; 8; 20; 21; 22]; item 15, rationale for choosing the reference standard (n = 6, 100%) [6; 7; 8; 20; 21; 22]; item 16, source of ground-truth annotations, qualifications and preparation of annotators (n = 3, 50%) [8; 20; 21]; item 17, annotation tools (n = 4, 67%) [7; 20; 21; 22]; item 18, measurement of inter- and intra-rater variability (n = 6, 100%) [6; 7; 8; 20; 21; 22]; item 20, how data were assigned to partitions, specify proportions (n = 1, 17%) [8]; item 21, level at which the partitions are disjointed (n = 6, 100%) [6; 7; 8; 20; 21; 22]; item 23, software, libraries, frameworks, and packages (n = 2, 33%) [6; 22]; item 24, initialization of model parameters (n = 3, 50%) [6; 8; 21]; item 26, method of selecting the final model (n = 5, 87%) [7; 8; 20; 21; 22]; item 27, ensembling techniques (n = 4, 67%) [6; 7; 8; 21]; item 28, metrics of model performance (n = 1, 17%) [20]; item 29, statistical measure of significant and uncertainty (n = 3, 50%) [6; 8; 20]; item 30, robustness or sensitivity analysis (n = 2, 33%) [20; 21]; and item 31, methods of explainability or interpretability (n = 5, 87%) [6; 7; 20; 21; 22].  
In the results section, 5 (83%) studies did not report the flow of the participants or cases (item 33) [6; 7; 8; 20; 22]. In addition, 3 (50%) studies did not present the demographic and clinical characteristics of cases (item 34) [6; 20; 22]. Moreover, only 1 (17%) study did not report the estimates of diagnostic accuracy and their precision (item 36) [8] and failure analysis of incorrectly classified cases (item 37) [20]. In the discussion section, only 1 (17%) study did not report the study limitations (item 38) [20]. Regarding the other information, none of the studies registered the number and name of the registry (item 40). Moreover, none of the CNN studies presented where the full study protocol can be accessed (item 41) [6; 7; 8; 20; 21; 22]. In addition, 2 (33%) studies did not show sources of funding and other support (item 42) [8; 22].
# Routing Protocols for Mobile Internet of Things (IoT): A Survey on Challenges and Solutions
## 5 Future Work
### Efficient Routing Protocol Supporting Various Traffic Patterns  
We note that the LLNs applications require a stable routing support for various traffic patterns e.g., point-to-multipoint (MP2P), node-to-node (P2P), and P2 MP (i.e., root to many nodes) with heterogeneous node capabilities [69]. It is also mentioned [29] that RPL optimizes the support for MP2P traffic patterns by efficiently constructing the DODAGs, however, other traffic patterns, such as P2P and P2 MP, need to route the pre-established DAG. Hence, the RPL does not provide efficient routing support, in addition to, efficient data delivery from long delays and lossy links while attributing various traffic patterns. To provide an efficient routing support in RPL, it is vital to address coordination among various nodes in order to support various kinds of traffic pattern in a single network. Note that the asymmetric nature of wireless links and traffic patterns have a significant impact on the performance of routing protocols; the real-world deployment fails [70] if the routing protocols do not consider the asymmetric traffic patterns.  
A major issue with the standard Trickle algorithm is the long 'listen-only' period where nodes only listen and receive messages instead of broadcasting the messages. Vital support for routing protocols is to address various issues, highlighted in Tables 1-5, under a single framework that has been addressed by various extensions of basic RPL. For example, the FLEA-RPL [60], CA-RPL [63], MI-FL [61], Modified RPL [45], Multiple-sinks [55], MoMoRo [64], Enhanced hand-off mechanism [65], and mRPL [46] address the issue with longer delay, either cause by ETX probing or hand-off delays, however, they fail to address the basic issue with Trickle timer algorithm.
# Machine Learning Approach for Arabic Handwritten Recognition
## 5 Conclusions  
We proposed a model for recognizing Arabic handwritten text. The system aims to identify Arabic handwritten text accurately by imitating the human brain to recognize text using machine learning approaches. The ResNet model was used for feature extraction, and BiLSTM-CTC sequence modeling was used for classification. Machine learning techniques are used to overcome traditional methods based on shallow learning and hand-engineered features. Moreover, machine learning approaches help overcome the challenges of recognizing Arabic handwritten text. A 3-gram language model was used in our system using the KenLM toolkit to improve the recognition accuracy of handwritten text.  
Our proposed model was evaluated on the KHATT and AHTID/MW datasets. The experimental results showed that our system had an impressive recognition accuracy, with a 27.31% WER and a 13.2% CER for the KHATT dataset and a 17.42% WER and a 6.6% CER for the AHTID/MW dataset.  
Although our proposed methodology for Arabic OCR has been successful, there are still certain limitations. The proposed study only employs a pretrained CNN model. Evaluating other transfer learning or transformer models is a future enhancement. Also, in future work, different datasets can be combined to reduce the generalizability problem.  
Conceptualization, methodology, supervision, and writing--review and editing, A.M.M.; data acquisition, methodology, experiment, and writing--original draft preparation, M.Y.A. and M.A.-H. All authors have read and agreed to the published version of the manuscript. This research received no external funding.  
Not applicable.  
The data presented in this study are openly available [19; 20].  
The authors
# An Ultra-Stable Polysaccharide Gel Plugging Agent for Water Shutoff in Mature Oil Reservoirs
## 3 Results
### Effect of Salinity on Gelation Behavior  
With the CTS concentration fixed at 2.0 wt%, the MBA concentration fixed at 0.6 wt%, and the pH maintained at 4.2, the salinity was varied at 3000 mg/L, 10,000 mg/L, 30,000 mg/L, 40,000 mg/L, and 50,000 mg/L to evaluate the gelation performance of the system under different salinity conditions. All gelation experiments were conducted at 120 \({}^{\circ}\)C.  
The relationship between salinity and gelation performance is shown in Figure 5. It can be observed that as salinity increased, the gelation time of the system progressively  
Figure 4: Effect of pH on gelation behavior (salinity: 30,000 mg/L; 120 \({}^{\circ}\)C).  
shortened. When the salinity increased from 3000 mg/L to 50,000 mg/L, the gelation time decreased from 19 h to 6 h. Additionally, gel strength improved with the increase in salinity.  
The effect of salinity on the gelation behavior of the system is likely related to the charge screening effect. After the addition of sodium chloride, Cl\({}^{-}\) ions interact with NH\({}_{3}\)\({}^{+}\) groups through charge screening, causing the CTS molecular chains to contract. This contraction increases the chances of a reaction between MBA molecules and the \(\alpha\),\(\beta\)-unsaturated carbonyl groups on CTS, thereby enhancing the cross-linking reaction rate and cross-linking density. As a result, gelation time is shortened and gel strength is increased.
# Mdpj _sciences_
## 5 Discussion and Countermeasures
### Countermeasures  
Table 1 summarizes the analysis of the DMRN Protocol and compares it with the existing protocols. Based on the comprehensive analysis and discussion of the DMRN Protocol, we propose the following countermeasures for designing a future PQC-enabled 6G AKA protocol:  
* Implementation of anti-replay techniques: future PQC-enabled 6G AKA protocols should incorporate robust anti-replay mechanisms to counter SUCI replay attacks. This is crucial to prevent attackers from reusing previously captured SUCI values for unauthorized authentication attempts. Potential solutions include integrating timestamps or one-time nonce values into the SUCI generation process. As an alternative, the HN can manage the database for previously used SUCI values for a specified period (e.g., 1 years) from which a given SUCI value's freshness can be quickly checked.
* Ensuring MAC freshness: The MAC generation process in the DMRN protocol should be improved to make the MAC value fresh. This can be achieved by integrating the UE's ephemeral public key \(pk_{U}\) into the MAC calculations. Such improvements would not only reduce the risk of replay attacks but also strengthen resistance against man-in-the-middle attacks.
* Addressing compromised or malicious SNs: To mitigate situations involving compromised or malicious SNs, the two values SUPI and \(K_{SEAF}\) transmission process should be modified. Specifically, the protocol should be adjusted to ensure that the is transmitted to the SN after the RES* is finally checked by the HN. This modification prevents malicious or compromised SNs from obtaining the anchor key without proper UE authentication.
* Adoption of hybrid PQC approach: While PQC approaches are essential for mitigating the threats posed by quantum computing, the current implementation status of PQC products raises reliability concerns. Therefore, we recommend adopting a hybrid PQC approach that integrates traditional cryptographic techniques with PQC methods. This balanced approach maintains current security levels while preparing for potential future threats from quantum computing.  
By implementing these countermeasures, future 6G AKA protocols can overcome the vulnerabilities identified in the DMRN protocol and provide enhanced security. These improvements will contribute to elevating the overall security posture of 6G networks, ensuring robust protection against both current and emerging threats, including those posed by advancements in quantum computing.
## 4 The Proposed Scheme
### User Revocation Phase  
In the case that the UE needs to quit the group or the system needs to revoke the illegal UE authentication in the unlinkable authentication, the algorithm in the user revocation phase is needed. For an illegal UE, the NCC has the right to disclose their real ID and other information through signatures they send out. The private key of the illegal UE can be calculated through the group master key \(gnsk:\langle\xi_{1},\xi_{2}\rangle\) and \((T_{1},T_{2},T_{3})\) in the signature. The NCC can find the real \(ID_{i}\) of the UE by comparing with the user information in UKL. For an illegal UE that requests to quit the group, the NCC performs the operations described above. After that, the NCC creates a revocation list (RL) that contains the key \((\varphi_{j},A_{j},RK_{j})\) of the \(UE_{j}\) to be revoked. The NCC sends the RL to each LEO. The LEOs save the RL and periodically broadcast the latest RL', which includes \(\left(\varphi_{j},A_{j}\right)\).  
A UE that receives the RL' updates its private key according to Algorithm 4, where \(m\) is the total number of tuples in RL'. Unrevoked UE must run this algorithm until all UEs in RL' are revoked. After completing the above steps, the unrevoked UE needs to update the pre-stored parameters \(\hat{e}(\hat{A}_{i},\hat{g})\) and \(\hat{e}(h,\ \hat{\omega})\). In addition, for offline UE, they need to request the latest RL' when they are online. Therefore, the revoked \(UE_{j}\) cannot obtain a new \(gsk_{j}\). The authentication will fail when the \(UE_{j}\) participates in group signature authentication again. When participating in batch authentication, \(UE_{j}\) will also be detected by the LEO, thus prohibiting its access to the network.  
```
Input:\(gsk_{i}\), \(RL=\left\{x_{j},A_{j}\middle|1\leq j\leq m\right\}\) Output:\(\left(\varphi_{i},\hat{A}_{i}\right)\)
```  
**Algorithm 4**Unrevoked User Update Parameters  
The user revocation process can be carried out offline, which reduces the burden on the UE and prevents delays caused by the LEO checking the RL operation during authentication. The performance analysis of [PERSON] et al. [30] showed that the revocation mechanism of SGS is effective. For the protocol that is unlinkable, this phase allows the UE to exit the group, better managing the network. Although user revocation brings additional computational overheads, it is acceptable and necessary.
# Robust Long-Term Visual Object Tracking via Low-Rank Sparse Learning for Re-Detection
## 2 Related Work
### DCF-Based Trackers  
Starting with the MOSSE algorithm [11], which adopts a correlation filter to a visual tracking task, discriminative correlation filter (DCF) based tracking gains extensive attention for its effectiveness and efficiency. Then, several recent works have been carried out to address the inherent limitations of the standard DCF-based tracking algorithms.  
For non-linear regression, [PERSON] et al. [12] learn the kernelized correlation filter (KCF) via a kernel trick. KCF achieves an extremely high tracking speed, because of the diagonalization of the cyclic matrix in the frequency domain. Besides, [PERSON] et al. [38] propose a multi-kernel correlation filter (MKCF), which makes use of the invariance-discriminative power spectrums of various features and improves the performance of the tracker further. For scale estimation, a scale pool has been introduced in DSST [13] and SAMF [14]. They can learn online using the target appearance samples at the scale pool and achieve accurate scale adaptive visual tracking. For boundary effects, [PERSON] et al. [17] introduce a spatial regularization component in DCF formulation to penalize the correlation filer coefficients during tracking. CSR-DCF [39] makes use of the spatial reliability map to adjust the spatial constraint and then guarantees that filter values are zero outside of the object bounding box. BACF [23] extracts real negative training samples from negative background blocks to further suppress the boundary effect. Besides, other improvements in DCF have also made much development in context-aware [40], temporal regularisation [21], deformable parts [41].
# Research on Data Link Channel Decoding Optimization Scheme for Drone Power Inspection Scenarios
## 3 Results
### Complexity  
Comparing the computational complexity of different decoding algorithms. The complexity calculation includes comparison (CMP) operations, exclusive OR (XOR) operations, multiplication (MUL) operations, and addition (ADD) operations. The computational complexities are presented in Table 3, where T represents the number of iterations. The complexities of NMS, NNMS, and SNNMS are given by [26], their complexities are compared to the new-SNNMS that we proposed in this study.  
We can observe that the shared-NNMS-CQ decoder has lower complexity compared with the NNMS decoder. Compared to SNMS, the shared-NNMS-CQ achieves better BER performance, but the MUL operation of the shared-NNMS-CQ is slightly more complex than that of SNNMS. Furthermore, the shared-NNMS-CQ introduces weight quantization to reduce the number of training parameters and further decrease computational complexity. Overall, the improved decoding algorithm presented in this paper exhibits superior performance.
# Converting Concurrent Range Index Structure to Range Index Structure for Disaggregated Memory
## 3 Method
### Search Layer and Data Layer in Range Index Structure  
General range index structures are composed of the _search layer_ and _data layer_, as shown in Figure 2. The search layer consists of internal nodes and provides a shortcut to the target node in the data node in the data layer. Thus, the nodes in the search layer do not include the data, and they only store the key and pointer to the child node. The data layer consists of data nodes (i.e., leaf nodes) in the range indexes. In the data node, the data are composed of key and value pairs where the value is typically the address of the data.  
There have been a lot of efforts to improve the concurrency level of range indexes in prior studies. Blink-tree [11] is the most widely known range index, improving the concurrency level by tolerating the transient inconsistencies of the range indexes. SkipList [12] is another index structure that can tolerate transient inconsistencies because of the insert and delete operation of internal nodes. Recently proposed hybrid range indexes [9; 10] improve the performance and scalability by tolerating transient inconsistencies between the search layer and the data layer. We exploit the concept of tolerating transient inconsistencies between the search layer and the data layer. In the range index structure for disaggregated memory, the client always needs to read the data node from the memory server to retrieve the up-to-date version. However, the search layer does not need to be an up-to-date version because it only provides the route to the data node. Instead, the client can access the target data node by traversing the data layer using the sibling pointer of the data node.
# Channel Measurement and Feasibility Test for Wireless Avionics Intra-Communications
## 2 Overview of IEEE 802.11 Physical Layer
### IEEE 802.11 Physical Layer and OFDM  
IEEE 802.11 is a set of media access control layer and physical layer protocol specifications for implementing wireless local area network (WLAN) in the industrial, scientific and medical (ISM) frequency bands (usually, 2.4 and 5 GHz). The original version of the standard was released in 1997(IEEE 802.11-1997 or legacy) and subsequent amendments (IEEE 802.11a IEEE 802.11b, IEEE 802.11g, IEEE 802.11n, IEEE 802.11 ac, etc.) have been done to support various system requirements. In most releases of IEEE 802.11 protocols, OFDM was widely adopted due to its robustness on the multi-path fading and its flexibility on operating bandwidth. Table 1 shows OFDM parameters used for most of IEEE 802.11 protocols.  
Note that high throughput or very high throughput modes with different OFDM configurations are specified and provided in recent releases (e.g., IEEE 802.11n or IEEE 802.11 ac). However, legacy mode based on Table 1 is mandatory due to backward compatibility and we mainly considered this legacy mode during our experiment.
# Research on the Influence of Backlash on Mesh Stiffness and the Nonlinear Dynamics of Spur Gears
## 4 Conclusions  
An improved mesh stiffness was proposed by taking the effect of backlash into account. The precise tooth profile equations with backlash were established to generate the gears. The potential energy method was employed to calculate the mesh stiffness. The calculation results indicated that when compared with the case of ignoring backlash, the mesh stiffness had an obvious decrease in the cycle of coming into the mesh to going out of the mesh. Moreover, the rate of decline showed a trend of decreasing first before increasing.  
Figure 10: The system response in terms of the dynamic transmission error of various backlash. (**a**) \(b=1.25b_{min}\); (**b**) \(b=1.5b_{min}\); (**c**) \(b=1.75b_{min}\); (**d**) \(b=2b_{min}\); (**e**) \(b=2.25b_{min}\); (**f**) \(b=2.5b_{min}\); (**g**) \(b=2.75b_{min}\); (**h**) \(b=3b_{min}\).  
To obtain an accurate stiffness function for numerical analysis, the mesh stiffness rather than the time-varying mesh stiffness was fitted in the form of Fourier series expansion, and the time-varying mesh stiffness was presented in terms of a piecewise function. The proposed fitting mesh used a low order Fourier series to obtain very high accuracy. The stiffness coefficient was also fitted by the Fourier series.  
The effects of backlash on dynamic transmission error were investigated, and the numerical results revealed that the gear system primarily performed a non-harmonic-single-periodic motion. The partially enlarged views indicated that the system also exhibited small-amplitude and low-frequency motion. For different cases of backlash, the low-frequency motion sometimes showed excellent periodicity and stability and sometimes showed a non-repetitive and aperiodic situation.  
The theory here focused on the impact of backlash on mesh stiffness and dynamic performance and established an indirect relationship between backlash and dynamic transmission error, which is expected in order to understand the mechanism of some unusual noise and to guide the design and manufacture of backlash in the future.  
Conceptualization, methodology, data curation, writing--original draft preparation, visualization, Y.X.; writing--review and editing, funding acquisition, K.H.; investigation, software, validation, F.X., Y.Y. and M.S.; supervision, Z.Z.  
This work was supported by the National Natural Science Foundation of China (51775156) and the Fundamental Research Funds for the Central Universities of China (JZ2018 HGTA0206, JZ2018 HGBZ0101).  
The authors declare no conflict of interest.