esa-sceva/satcom-chunk-collection huggingface dataset:
# A New Multivariate Approach for Real Time Detection of Routing Security Attacks in VANETs
## 1 Introduction
Detect the occurrence of attacks by continuously verifying the conformity of the datasets to the multivariate normality assumption by computing correlation coefficients and comparing them against thresholds representing the normal critical values. 4. Demonstrate the relevance of employing data rescaling techniques in improving the data sensitivity to the normality conformity analysis, by comparing the outcomes of different rescaling techniques: Z-Score Normalization (ZSN), Min-Max Normalization (MMN), and Normalization by Decimal Scaling (NDS). 5. Evaluate the proposed scheme using more realistic scenarios based on a realistic mobility model. To demonstrate the applicability of the proposed approach, implementation of MVSDS with black hole attack is presented. Two scenarios are simulated: one normal AODV without attacks and a second with AODV under black hole attack. The simulation of these scenarios is conducted by combining two simulators: the road traffic generator SUMO (Simulation of Urban Mobility) [14] and the network simulator NS-3 [15]. SUMO is used to create mobility trace files based on a real map extracted from OpenStreetMap. These trace files are then used as input by the network simulator NS-3. The findings reveal that our approach implemented in the Matlab environment [16] can detect AODV abnormal behavior in a real time by involving multiple network traffic characteristics simultaneously. It can further be applied to any VANET routing protocol without making any additional changes in the routing algorithm. The simulation results are promising since our approach needs fewer computational requirements with a high capability to analyze multiple network traffic characteristics simultaneously. As far as we know, our approach may offer an innovative solution for the detection of routing security attacks in VANETs. This manuscript is organized into seven sections: In the next section, we introduce the background information. In Section 3, we present the related works of the previous literature. Section 4 describes the proposed approach, while the implementation details are given in Section 5. Section 6 provides an analysis of the results. Concluding remarks and future research directions are given in Section 7.
## 5 Proposed Protocol
### Security Requirements  
In order to fulfill these security requirements of WSNs, we consider data integrity, source authentication, data confidentiality and data freshness in applying cryptographic algorithms to the proposed protocol. As shown in Figure 6, eight messages are involved in our protocol. Evaluating the security requirement of each message is vital in equipping every involved party with adequate tools to endorse a secure and robust yet efficient protocol. Table 1 summarizes the security requirements of each message. The first message, **adv**, requires data integrity protection to prevent any intruder from altering the identity of the announcing node. The impact can be that some nodes try to join a non-existent cluster. At the end of the setup phase those nodes may end up without a CH (orphans). In order to gain network information, it is possible for intruders to advertise themselves as a CH. Therefore a source authentication feature is needed as well. Data freshness is also required in order to avoid reply attacks. The LEACH protocol cannot detect if a particular node has sent an **adv** message twice or more in a round. An intruder can rebroadcast the **adv** messages and some nodes may join non-existent clusters. This situation can delay and disrupt the cluster formation stage. The join request message, the **join_req**, requires source authentication in order to prevent illegitimate nodes from joining the network. Malicious cluster members can send fake sensor readings to give inaccurate network information. Crowding the timeslots of the TDMA schedule can be another option for intruders by sending many fake **join_req** messages. It can delay the actual sensor data gathering. Therefore source authentication is important. Data integrity is also required so that unwanted alterations can be detected. The impact if the id of the sender is changed to another node's id is that the CH will incorrectly recognize its cluster members and later on falsely assign the timeslot to the wrong node. If the id of the CH is changed, then the joining node may falsely join another cluster or ends up as an orphan node. In dealing with replay attacks which takes place at later rounds, data freshness is required. Except for the schedule part that does not need data confidentiality, the **sched_seed_permut** message needs data integrity, source authentication, data confidentiality and data freshness. This message contains the TDMA schedule for a cluster, pattern seeds for the member nodes to generate lookup tables and the mapping permutation of the NOVSF-BH technique. Their security requirements are detailed as follows. The communication within a cluster can be disrupted just by changing the schedule for the cluster members. Therefore the schedule needs data integrity protection. Without source authentication, it cannot be guaranteed that the schedule comes from an authorized CH. Anyone can send fake schedules and disrupt the communication within a cluster. As some nodes may join the same CH at the later round, replaying an old schedule may affect those nodes which leads to communication disruption.
# Transfer Convolutional Neural Network for Cross-Project Defect Prediction
## 3 Methodology
### Program Parsing and Vector Mapping  
Our model takes an input of Java files of the source project with known labels (i.e., defective or clean) and unlabeled Java files from the target project. Related work proved that ASTs can be used to detect source code and defects [22], so in this paper, we adopt an AST as the representation of source code. It is worth mentioning that ASTs can not only express the syntax features, but also the semantic features of the source code [8].  
In this step, _Javalang_ ([[https://pypi.org/project/javalang/0.9.2/](https://pypi.org/project/javalang/0.9.2/)]([https://pypi.org/project/javalang/0.9.2/](https://pypi.org/project/javalang/0.9.2/))) was applied to parse the Java files and generate corresponding token vectors. Each element in Java files can be represented as a node in the tree. Table 1 shows the categories and types of nodes we used. Referring to [9], considering that the names of methods and variables are usually project-specific, we use node type (e.g., MethodDeclarations and ClassInvocation) to label nodes rather than the specific name. Furthermore, the token vectors extracted by _Javalang_ cannot be directly used as the input of our TCNN model, referring to [8], so we created a unified mapping dictionary between the node types and the integers to convert the token vectors to integer vectors. In addition, because CNN requires input vectors to have the same length, all input vectors were padded with zeros to the length of the longest vector.  
Figure 2: Overview of our TCNN framework to perform CPDP. AST, abstract syntax tree; TCNN, transfer convolutional neural network.
## 3 System Design
### Compression Module  
The compression module provides a transparent compression function to the upper layer. The appropriate compression algorithm is selected to (de)compress the data according to the preset configuration of the user. The overall design of the compression module includes three parts: concurrent compression streams, the algorithm implemented in the software, and the GZIP library assisted by the QAT accelerator.  
**Concurrent compression stream.** Compression streams provide a compression entry that supports concurrent read and write operations, enabling the worker thread to concurrently execute the second half of the process. In addition, the compression stream maintains a buffer to store the compressed data. During compression, there is a small probability of data inflation. Therefore, the compressed stream buffer space is set to 8k, twice the size of the virtual page. By default, the GZIP algorithm library based on the QAT accelerator is used as the compression algorithm in the compression stream. If users have special requirements, they can select a compression algorithm for the compression stream based on the application scenario.
# Impact of Gait-Synchronized Vibrotactile Sensory Feedback on Gait in Lower Limb Amputees
## 1 Introduction  
Available lower limb high-tech prosthetic devices currently do not provide natural sensory information on movements or ground characteristics, which might explain the unphysiological walking patterns with the prosthetic leg [1; 2; 3; 4]. Several studies have shown that sensory feedback from the remaining extremity reduces the risk of falling, cognitive efforts, metabolic cost and fatigue of normal physical activity as well as phantom limb pain [1; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14]. The key qualities that users require from such sensory systems are for them to elicit sensations of touch or proprioception as naturally as possible by delivering complex signals to the nervous system that would be produced by skin, muscle, and joint receptors [15; 16; 17; 18].  
Sensory feedback systems can be divided into two major groups: non-invasive and invasive/implantable devices. While invasive systems (e.g., implantable neural electrodes) can restore homology and somatotopy of the sensation, which enhance the acceptance and use of the prosthetic device [5], they lack biocompatibility and authenticity, posing highrisks due to invasiveness [17]. The major advantage of non-invasive feedback devices is that they stimulate the body externally, usually through the skin, eliminating the risks associated with invasiveness or surgery. However, without surgical augmentation (e.g., Targeted Sensory Reinnervation) these devices are not able to restore somatotopy of the sensation [17]. Since addressing the skin of the missing limb is not possible post-amputation, cutaneous stimulation must be applied to alternative body sites. Establishing an association between this cutaneous stimulation and the amputated limb generally requires intensive training with the feedback system--a process known as \"sensory remapping\" [17]. Additionally, non-invasive devices typically transmit sensory information through a single sensory modality (e.g., pressure, vibration or electrical stimulation), lacking authenticity and thus failing to restore sensory homology.  
Several studies have evaluated the effect of different non-invasive sensory feedback systems on healthy subjects and amputee patients, including mechanotactile [19; 20; 21; 22; 23], vibrotactile [24; 25; 26; 27; 28; 29; 30] and electrotactile feedback [31; 32; 27; 31]. For vibrotactile feedback, however, most studies have focused on upper limb prosthetics [20; 24; 25; 26; 27; 29] or have examined static effects in lower limb amputees, such as improved standing balance and postural control [14], rather than its effects on dynamic tasks like gait [30]. Even though sensory feedback is the subject of the research of numerous prosthetic research groups, no feedback system has yet become established in everyday use or availability [15; 17]. Herein, we investigate the effect of a supplementary feedback system that encodes real-time pressure during walking into vibrotactile stimulation of the residual limb's skin.
## 4 Simulation Results and Discussion
### _Proportional Fairness Analysis_  
Figure 8 describes the normalized rate ratios per user for a system of 16 users. The AWGN noise power density is \(-80\) dB\(\cdot\)W/Hz, BER = \(10^{-6}\). The normalized rate ratio is defined as _R\({}_{k}\)_/_2R\({}_{k}\)_. For each user in Figure 8, there are four bars, from left to right, the first bar represents the required proportionality \(\varphi_{k}\), and the other three bars represent the obtained proportionality by the proposed method, and the linear and root-finding methods. The proposed method ACO-SPA has higher proportional fairness than other two methods. This is due to the reasons that in the root-finding method, the simplification of power allocation relaxes the proportionality. In addition, in the linear method, it assumes that the proportion of subcarriers assigned to users is equal to their initial required data rates. This assumption causes the relaxation of the proportionality constraints. In the proposed method, the power allocation algorithm has the controls over power distribution across subcarriers for each user, which has no impact on proportional fairness among users. Figure 9 illustrates the [PERSON]'s fairness index of system _versus_ the number of users. The proposed method ACO-SPA obtains the strict system fairness with the [PERSON]'s fairness index identically equal to 1. The ACO-EQ method is that the total power is equally assigned to the subcarriers after the subcarrier distribution by the proposed ACO algorithm. As the equal power allocation algorithm does not take full account of the proportional fairness constraints, it achieves the low system fairness.  
Figure 7: The sum rate _versus_ average SNR.
# The Applications and Challenges of Digital Twin Technology in Smart Grids: A Comprehensive Review
## 3 Digital Twin Technology in Smart Grids
### Core Concepts and Implementation Requirements  
Before diving into Digital Twin implementation requirements, it is important to understand the different grid types in which DT technology can be applied. The evolution of grid technology has progressed through several distinct stages, each with unique characteristics and capabilities that influence DT integration.  
The conventional electric grid is designed around a centralized power generation station that connects transmission and distribution networks through electromechanical systems. It delivers electricity across extensive distribution areas via centralized one-way transmission and distribution lines controlled by electrically operated mechanical  
Figure 6: Progress in electrical grid innovations.  
devices. This centralized setup features limited sensors, causing control challenges. As a result, the monitoring of power distribution and transmission is typically conducted manually, and the system lacks self-healing capabilities. The one-directional nature of this energy system contributes to significant transmission and distribution losses, increases the risk of grid overheating incidents, and complicates fault detection due to manual monitoring [72]. These issues can lead to frequent power disruptions, extended recovery times, and substantial economic losses.  
In response to these limitations, the smart grid has emerged as an advanced energy infrastructure that enhances the capabilities of previous grids, making them faster, more intuitive, and collaborative. It integrates the roles of all participants, including producers, consumers, and utilities, to ensure reliable, cost-effective, and efficient energy distribution. Unlike the traditional grid, which is characterized by centralized generation and high transmission losses, the smart grid employs a bidirectional exchange of data and electricity, supporting both large-scale and localized power generation methods [73]. The next evolution in the grid technology is the Virtual Power Plant (VPP), which is a system hosted in the cloud that aggregates multiple types of power sources, functioning as a cohesive energy plant. VPPs are integral to enhancing the stability and intelligence of smart grids by utilizing distributed energy resources (DERs). They rely on sophisticated software systems to automatically manage, integrate, dispatch, and store electricity. Essentially, VPPs serve as the infrastructure for integrating DERs, allowing each connected resource to interact and synchronize like a neural network, akin to the Internet of Things.
# Bayesian Estimation of Simultaneous Regression Quantiles Using Hamiltonian Monte Carlo
###### Abstract  
The simultaneous estimation of multiple quantiles is a crucial statistical task that enables a thorough understanding of data distribution for robust analysis and decision-making. In this study, we adopt a Bayesian approach to tackle this critical task, employing the asymmetric Laplace distribution (ALD) as a flexible framework for quantile modeling. Our methodology implementation involves the Hamiltonian Monte Carlo (HMC) algorithm, building on the foundation laid in prior work, where the error term is assumed to follow an ALD. Capitalizing on the interplay between two distinct quantiles of this distribution, we endorse a straightforward and fully Bayesian method that adheres to the non-crossing property of quantiles. Illustrated through simulated scenarios, we showcase the effectiveness of our approach in quantile estimation, enhancing precision via the HMC algorithm. The proposed method proves versatile, finding application in finance, environmental science, healthcare, and manufacturing, and contributing to sustainable development goals by fostering innovation and enhancing decision-making in diverse fields.  
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Footnote †: journal:  
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Footnote †: journal:  
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Footnote 1: INRAE, URI204, AgroParisTech, 147 Rue de l'Universite, 75338 Paris, France 1  
Footnote 2: College of Engineering and Technology, American University of the Middle East, Egalila 54200, Kuwait 2  
Footnote 2: Correspondence: [EMAIL_ADDRESS]  
simultaneous quantile regression; Bayesian approach; Hamiltonian Monte Carlo; estimation; asymmetric Laplace distribution
## 2 Materials and Methods
### Data Sources
#### 2.2.3 Elevation and Land Use/Land Cover Data  
The study area's elevation was determined using the publicly accessible shuttle radar topographic mission (SRTM) digital elevation model (DEM) from the USGS earth explorer platform. The DEM has a spatial resolution of 90 m. Subsequently, the data at this resolution were averaged to achieve a finer 10 m resolution as demonstrated in Figure 1b. Additionally, land use/land cover data from the land development department (LDD) of Thailand were incorporated. These raster-format data cover specific regions, including Bangkok, Pathum Thani, Samut Prakan, Ayutthaya, Lopburi, and Nakhon Ratchasima, spanning the years 2000-2019. The data are classified according to the Level 1 LDD standard classification criteria, comprising five classes as illustrated in Figure 1c: built-up area (U), agricultural land (A), forest area (F), water body (W), and miscellaneous land use (M). This classification aids in comprehending regional land use patterns and their potential impact on local temperatures.
# Mobility Management of Unmanned Aerial Vehicles in Ultra-Dense Heterogeneous Networks
## 4 Research Challenges
### Transmission Protocols  
Data in UAV-based connected networks must be rerouted from one serving UAV BS to another serving BS because UEs switch from one BS to another during the HO process. This is an important point that makes the transmission protocol important in UAV-basedconnected networks and should be highlighted. Several companies have successfully filed patent applications detailing how UAVs to scan and acquire data while dropping data packets, such as a queuing delay and transmission delay (QDTD) routing protocol. This solution, on the other hand, employs a complex processing method that necessitates more computation time, resulting in data delays and a decrease in data throughput [80]. Another protocol is an adaptation of the distance routing effect algorithm for mobility (DREAM) protocol, which includes a location service, a local database, and a routing agent. The location service keeps track of each node's location. To compute location, the distance effect given by the difference in velocities of two nodes is used [81]. The Media Access Control (MAC) layer is another protocol, and directional antennas are used at the top and bottom of the aircraft. The UAV detects the medium to determine whether or not there is any active communication [82]. TCP/IP and other traditional transmission methods will be insufficient for UAVs. As a result, new procedures based on the mobility characteristics of UAVs must be developed [83].
## 6 Results and Discussion
### Discussion  
In this study, a model based on DADER was developed to perform scheduling at the planning stage of construction projects. The model was applied to a case study to derive results. Despite the current efforts in the construction industry to enhance scheduling efficiency using building information modeling (BIM), digital twins, and artificial intelligence (AI), the persistent challenge of addressing the level of detail led to the development of DADER. This model aims to effectively address the issue of level of detail in construction scheduling and make it applicable to real construction sites.  
The application of the model in a case study revealed that utilizing our developed model enables the generation of schedules at a detailed activity level, minimizing costs within the target duration. Additionally, validation through expert surveys confirmed the model's efficiency in terms of cost, onsite applicability, and task efficiency. Thus, our developed model is identified as a solution to bridge the gap between planning and onsite execution in construction scheduling.  
However, it is essential to acknowledge the limitations of this study. The model falls short of achieving a scheduling implementation level suitable for real construction sites. The actual construction environment introduces numerous variables such as weather conditions, material transportation delays, and site-specific factors like noise. Given that our model was developed under the most ideal conditions, future research aims to refine the model to a level applicable in real construction settings. This refinement would address various disputes and policy challenges arising from scheduling issues in the construction industry.
# Efficacy of Herbal Extracts-Based Nano-Formulations in Extending Guava Fruit Shelf-Life
## 1 Introduction
Phytochemical studies showed that ajwain is rich in phenolics, glycosides, alkaloids, flavonoids, tannins, and steroids. Thus, these two herbs were used prepare extracts for making edible coatings. Ajwain and giloy have antibacterial properties which help in preventing fruit damage due to bacterial infection. Thus, treatment of guava with edible coatings based on herbal extracts having antibacterial properties will help in maintaining fruit quality for longer periods by preventing bacterial contamination. Nowadays, nanotechnology provides new avenues for the transfer of active components of plant extracts like polyphenols, vitamins, and antioxidants. Nanotechnology constitutes particles and formulations of size ranging between 100-500 nm [19]. Nanoparticles have a higher surface area to volume ratio compared to large particles, conferring high stability and biological activity. Temperature has an impact on fruit quality. Low temperatures maintain the fruit quality for longer with improved shelf life. The effect of edible coatings with lower temperature in increasing shelf life has been studied in guava, such as use of carnauba wax and xanthan gum coating at 10 \({}^{\circ}\)C which enhanced the shelf life of fruit by up to 30 days [20]. In the present study, ajwain and giloy plant extracts were prepared which were then used for nanoformulations synthesis. Sodium alginate biopolymer was used along with CaCl\({}_{2}\) which results in synthesis of a calcium alginate complex. Calcium acts as a scrosslinker and results into herbal extract entrapment inside the alginate and calcium crosslink. Properties of herbal extracts, such as antioxidant, antibacterial and nutritive features, will further improve the efficiency of synthesized nanformulations. The synthesized nanformulations were tested for antioxidant and antibacterial properties. Then, nanoformulations treatment on guava was performed at two temperatures, viz. 25 \(\pm\) 2 \({}^{\circ}\)C and 32 \(\pm\) 2 \({}^{\circ}\)C on guava (Hisar Surkha) fruit and analyzed for physiological changes in guava fruit. Temperature impacts the fruit shelf life greatly and thus different temperatures are used for fruit storage.