esa-sceva/satcom-chunk-collection huggingface dataset:
# An Efficient VQ Codebook Search Algorithm Applied to AMR-WB Speech Coding
###### Abstract  
The adaptive multi-rate wideband (AMR-WB) speech codec is widely used in modern mobile communication systems for high speech quality in handheld devices. Nonetheless, a major disadvantage is that vector quantization (VQ) of immittance spectral frequency (ISF) coefficients takes a considerable computational load in the AMR-WB coding. Accordingly, a binary search space-structured VQ (BSS-VQ) algorithm is adopted to efficiently reduce the complexity of ISF quantization in AMR-WB. This search algorithm is done through a fast locating technique combined with lookup tables, such that an input vector is efficiently assigned to a subspace where relatively few codeword searches are required to be executed. In terms of overall search performance, this work is experimentally validated as a superior search algorithm relative to a multiple triangular inequality elimination (MTIE), a TIE with dynamic and intersection mechanisms (DI-TIE), and an equal-average equal-variance equal-norm nearest neighbor search (EEENNS) approach. With a full search algorithm as a benchmark for overall search load comparison, this work provides an 87% search load reduction at a threshold of quantization accuracy of 0.96, a figure far beyond 55% in the MTIE, 76% in the EEENNS approach, and 83% in the DI-TIE approach.  
vector quantization (VQ); binary search space-structured VQ (BSS-VQ); immittance spectral frequency (ISF); adaptive multi-rate wideband (AMR-WB); speech codec; VoIP +
Footnote †: journal:  
_Article_  
An Efficient VQ Codebook Search Algorithm Applied to AMR-WB Speech Coding
# Multi-Objective Optimization of Three-Stage Turbomachine
## 5 Simulation Results of Optimization Algorithms  
For each algorithm, 10 independent runs were conducted and the runs that converged to the lowest fitness function value were plotted over 1000 iterations, as shown in Figure 6. It should be noted that the scale is logarithmic. As observed, although the non-metaheuristic PS yielded the best result, the metaheuristic ABC and DE followed closely with commendable performances. Fitness function values that converged were below 1 for all algorithms. Decision analysis is necessary to select the most suitable method among these outputs, as individual behaviors may vary slightly despite similar fitness function values. The optimal approach for this evaluation is the statistical assessment of the algorithms. Table 5 presents the standard deviations alongside the optimal values obtained from the algorithms. Having a lighter rotor correlates with reduced potential energy and leads to a more efficient rotor design. The results indicate that the PS algorithm produced the lightest rotor.  
Another critical aspect for turbomachines is minimizing the variation in blade tip clearance values within the operational range. Variations in blade tip clearance directly impact the performance of the turbomachine. In this context, the ABC algorithm yielded the rotor with the least deflection.  
Considering that turbomachines operate at high speeds, the magnitude of forces experienced in the bearings is crucial. Repeated exposure to these forces can significantly affect the operational lifespan of the machine. The results show that the BH, GSA, and HHO algorithms recommended a rotor structure that experienced high forces on the first bearing.  
Another important consideration is to keep the natural frequency as far away as possible from the operating speed range. In contrast, the SA algorithm proposed the rotor with the highest natural frequency. Regarding standard deviation, the PSO algorithm provided the most reliable results, while HHO exhibited the highest standard deviation among the optimization algorithms.  
The preferred algorithm should closely approach all objective functions with a low standard deviation. Since optimization problems generally involve time-consuming improvement processes, it may not be feasible to test all algorithms comprehensively in real-world scenarios. If metaheuristic algorithms are to be evaluated, ABC can be considered the best performer. However, it should not be overlooked that PS also demonstrated superior performance, outperforming many metaheuristic algorithms.  
After evaluating the fitness function, a detailed assessment of each algorithm's best solution was conducted. The optimal solutions were evaluated in terms of their frequency response function (FRF) and rotordynamic characteristics, as discussed in the subsequent subsections.
## 4 Discussion  
In this study, the issue of modeling a 3D latticed model of a hip implant was addressed. CAD modeling of 3D latticed hip implants is complicated and always consumes much time and expense related to computing power, which makes simulation studies hard to perform. The authors found that the most effective way is to replace the geometrically latticed model with a bulk model that has the same numerical properties in the simulation software. The main numerical mechanical properties that should be used to define the material in this case are the Young's modulus and Poisson's ratio.  
In [23], [PERSON] et al. presented a basis for the selection and practical implementation of surrogate models by using mesh-free surrogate models for structural mechanic FEA simulation. The study suggested that mesh-free surrogate models overcome the drawback that is represented by the need for more computational effort in case a higher-resolution simulation is needed. Lower geometrical complexity could be applied with such models, which would save both the time and cost of the numerical solution. On the other hand, we performed meshed numerical calculations where the solution accuracy was preserved and, yet, the simulation time and computation capacity were reduced.  
In our study, the simulation processing of latticed hip implants was optimized by the integration of latticed model's properties into the bulk model's properties, which accelerated the solution procedure without having to incorporate a machine learning model to reduce the variables in the process. [PERSON] et al. [25] tried to combine computational approaches with machine learning-based approaches in order to reduce costs and accelerate design creation.  
Using a surrogate model to replace a latticed model depends, however, on many factors. Firstly, the number of variables incorporated into the simulation process--two in this study--can make the process more efficient. Secondly, the computation capacity that is available should be considered; a computer's RAM memory and processors can define whether the need to reduce a simulation's load is worthwhile. Lastly, the accuracy level that is needed in the simulation is important; the desired accuracy level can define whether the use of a particular model is suitable or not.
## 1 Introduction  
Global market data have shown 10.4% compound annual growth rate in gluten-free sales between 2015 and 2020 because of the incidence of celiac disease and other gluten-associated allergies [1, 2]. The gluten-free market today provides a variety of foods that can be eaten safely by patients suffering from celiac disease [3]. Bread is one of the major staple foods [4, 5]. In general, breads formulated with gluten-free raw materials have low nutritional properties, poor taste, and are of inferior quality. In the absence of gluten, dough presents poor rheological properties (viscoelasticity) and is unable to develop a protein network, affecting the final quality of gluten-free bread [6, 7].  
The replacement of gluten is one of the most challenging problems in food technology [8]. The use of alternative ingredients including starch, hydrocolloids, protein, enzymes, emulsifiers, and fibers in the preparation of gluten-free bread can improve the texture, mouthfeeel, acceptability, shelf life, and nutritional properties of the products. Inaddition, the viscoelastic properties of gluten can be imitated [9; 10; 11; 12]. Similar effects can be expected when adding fruit and vegetable by-products to bread [13].  
Some by-products from fruit and vegetable processing are appropriate sources of nutrients and functional ingredients for gluten-free products, and could be used as low-cost ingredients. Fruit and vegetable by-product processing includes pomace, peel, and seed fractions, which are good sources of functional substances. These products offer beneficial bioactive compounds such as carotenoids, enzymes, polyphenols, oils, vitamins, dietary fibers, amino acids, and proteins for gluten-free products [14; 15; 16]. Dried fruit pomace can be used in bakery products to substitute flour, sugar, or fat, increasing the amount of fiber and antioxidants and reducing the energy consumption [8]. Each fruit and vegetable contains approximately 5-50% of peel/skin by-products, which are rich in cellulose, hemicellulose, and lignin as major constituents and may also contain other functional groups of lignin, including aldehydes, ketones, alcohols, carboxyl, hydroxide, and phenols [17]. In addition, antioxidant components, flavonoids, minerals, and vitamins are also available in such by-products [18; 19; 20].  
Many studies are in progress to evaluate the effects of fruit and vegetable by-products (such as orange peel, pomegranate peel, mango peel, grape peel, and potato peel) on wheat bread to improve the texture and quality of the final products [21; 22; 23], but only a few studies have been conducted on the utilization of fruit and vegetable peels for gluten-free bread products.  
Thus, in this study we evaluated the rheological and gluten-free properties of bread prepared with corn and chickpea flours and enriched with two different types of pomace (from orange and apple) and four different types of peels (from tomato, pepper, prickly pear, and prickly pear seeds). These breads were compared with the non-enriched gluten-free bread and wheat bread.
# An Opportunistic Network Routing Algorithm Based on Cosine Similarity of Data Packets between Nodes
## 3 An Efficient Forwarding Strategy Based on Cosine Similarity between Nodes
### Node Definition and Similarity Calculation
When the degree of similarity between the current node and its neighbor node is greater than the lower threshold \(\alpha\), the neighbor node is taken as a candidate node for the next hop._  
If the similarity between the current node and all its neighbor nodes is less than that of the lower threshold \(\alpha\), the neighbor node with the greatest similarity will be selected for information transmission. **Definition 6**. : _The upper threshold of node similarity (\(\beta\)). In the OppNet with people as the mobile carrier, if the similarity between the current node and one of its neighbor nodes is greater than the upper threshold \(\beta\), it shows that the social properties of the two nodes are very similar. It is possible that their movement trajectories and the nodes they can reach are not much different. Therefore, it is not necessary to use this neighbor node as a candidate node for the next hop._  
If the degree of similarity between the current node and all its neighbor nodes is greater than the upper threshold \(\beta\), the neighbor node with the smallest similarity is selected for information transmission. If the similarity between the current node and some neighbor nodes are less than the lower threshold \(\alpha\), and the similarity with rest of the neighbor nodes is greater than the upper threshold \(\beta\), Then, the neighbor node with the greatest similarity is selected as the next hop in all neighbor nodes whose similarity is less than the lower threshold \(\alpha\). In all neighbor nodes whose similarity is greater than the upper threshold \(\beta\), the neighbor node with the smallest similarity is selected as the next hop node for information transmission.
###### Abstract
Thus, the architecture can fuse sensor detections of the same person realized in non-adjacent sites of a big area and also allows one to set up a network of installations covering different sites of the same infrastructure. Other than informing the security room in real time, the C&C automatically supplies alerts to a indoor localization system dispatching images of the person to be altered on the smart glasses worn by the security guards, thus enabling their timely reaction on the field. The architecture comprising the C&C and the two video systems, named INSTEAD (Integrated SysTem for Early Thread Detection), has been implemented for the NATO-SPS funded [6] DEXTER program and has been successfully tested in a Big City Trial (BCT) at a metro station in Rome, both when integrated with two real detectors of weapons and explosives and as a stand-alone system. The assessment of INSTEAD in the controlled trials is detailed in [7], whereas a preliminary study of INSTEAD was presented in [8]. This paper describes the software architecture of the C&C implementation, which is modular, as it integrates completely decoupled components. Two generic types of video sensor data fusion methods are implemented: one suitable for sensors exclusively targeted on movable objects and the other for sensor systems that use their own video system to work towards a target. Thus, these methods can be applied to various sensors, and not only those used for DEXTER. The loosely coupled component communication model and a generic data structure for sensor messages allow extension of the software with additional components. The software design and the results of further experiments performed in the real environment using less constrained scenarios than those presented in [7] allow one to demonstrate flexibility and re-use of the system in different deployments. Other relevant quality aspects of the software are also discussed. The rest of the paper is organized as it follows. Section 2 presents related work. Section 3 provides the reference system architecture where the C&C has been implemented as part of the INSTEAD system, and the description of the DEXTER deployment is used as a case study. Then, the C&C is detailed in Section 4. Section 5 presents the experimental results, while a discussion on quality aspects of the system is presented in Section 6. Finally, Section 7 summarizes the conclusion and suggestions for future work.
###### Abstract  
With the proliferation of mobile devices, the amount of social media users and online news articles are rapidly increasing, and text information online is accumulating as big data. As spatio-temporal information becomes more important, research on extracting spatiotemporal information from online text data and utilizing it for event analysis is being actively conducted. However, if spatiotemporal information that does not describe the core subject of a document is extracted, it is rather difficult to guarantee the accuracy of core event analysis. Therefore, it is important to extract spatiotemporal information that describes the core topic of a document. In this study, spatio-temporal information describing the core topic of a document is defined as'representative spatio-temporal information', and documents containing representative spatiotemporal information are defined as'representative spatio-temporal documents'. We proposed a character-level Convolution Neuron Network (CNN)-based document classifier to classify representative spatio-temporal documents. To train the proposed CNN model, 7400 training data were constructed for representative spatio-temporal documents. The experimental results show that the proposed CNN model outperforms traditional machine learning classifiers and existing CNN-based classifiers.  
convolution neural network; spatio-temporal document; document classification; big text data +
Footnote †: journal: Medical Image Analysis  
[PERSON] _et al._
# Static Analysis for ECMAScript String Manipulation Programs
## 5 Abstract Semantics of ECMAScript String Operations
### Abstract Semantics of \(\mathsf{StartsWith}\)  
The abstract semantics of \(\mathsf{startsWith}\) takes as input two automata and checks whether a string of the language of the first automaton starts with a string of the language of the second one. The abstract semantics of \(\mathsf{startsWith}\) is captured by the function \(\mathsf{SW}^{\sharp}:\textsc{Dfa}_{/\equiv}\times\textsc{Dfa}_{/\equiv} \rightarrow\mathbb{B}^{\sharp}\), computed by Algorithm 2, where \(\mathsf{maxString}:\textsc{Dfa}_{/\equiv}\to\textsc{Dfa}_{/\equiv}\) returns the (minimal) automaton recognizing the longest string of the automaton given as input and \(\mathsf{isSinglePath}:\textsc{Dfa}_{/\equiv}\rightarrow\{\mathtt{true}, \mathtt{false}\}\) checks whether the input automata \(\mathtt{A}=(Q,\Sigma,\delta,q_{0},F)\) respect the following condition: \(\delta=\bigcup_{i\in[0,|Q|]}(q_{i},q_{i+1},c)\). Informally, a single-path automaton is an automaton where, if we sort the strings of its language from the shortest to the longest, each string is a prefix of the next one. An example of a single-path automaton is reported in Figure 8(b) where it is graphically clear that each state, excluding the initial and last one, have one incoming and one outgoing transition. Since the longest string in a single-path automaton has, as prefix, all the others of the language, it is sufficient to check, for an automaton \(\mathtt{A}\), if it starts with only the former. For example, let \(\mathcal{L}(\mathtt{A})=\{softer\}\) and \(\mathcal{L}(\mathtt{A}^{\prime})=\{s,so,soft\}\). The string \(s\) is prefix of \(so\), which is in turn prefix of \(soft\) so \(\mathtt{A}^{\prime}\) is a single-path automaton. Therefore, in this case, it is sufficient to check if \(softer\) starts with only \(soft\) (the longest string of \(\mathcal{L}(\mathtt{A}^{\prime})\)) since, being \(\mathtt{A}^{\prime}\) single-path, the other strings (\(s\) and \(so\)) are consequently prefix of \(softer\). Instead, consider \(\mathcal{L}(\mathtt{A}^{\prime})=\{s,no\}\). It would be impossible for a string to start with both of them since there is no prefix relation between them. Algorithm 2 takes as input two automata denoted by \(\mathtt{A}\) and \(\mathtt{A}^{\prime}\). Lines 1-9 handle some corner cases. If \(\mathcal{L}(\mathtt{A}^{\prime})=\{\varepsilon\}\), \(\{\mathtt{true}\}\) is returned, since any string starts with \(\varepsilon\) (lines 1-3). If none of the prefixes of \(\mathtt{A}\) is recognized by \(\mathtt{A}^{\prime}\), meaning that none of the strings recognized by \(\mathtt{A}\) start with a string of \(\mathtt{A}^{\prime}\), we can safely return \(\{\mathtt{false}\}\) (lines 4-6). Finally, if at least one of the input automata have cycles, we return \(\{\mathtt{true},\mathtt{false}\}\) (lines 7-9). Lines 10-17 determine if any string of \(\mathtt{A}^{\prime}\) is the beginning of any string of \(\mathtt{A}\), otherwise \(\top_{\mathsf{Bool}}\) is returned.
## 1 Introduction
The results showed that the maximum von Mises stress is reduced to 963.435 MPa. These studies mainly focus on the shape design of holes and have achieved good results, but the selection and discussion of optimization algorithms are relatively few. Actually, the optimization algorithm has a significant impact on the final scheme. An appropriate optimization algorithm will help designers get a good design scheme at a fast speed. Nowadays, swarm intelligence has been widely used to find globally optimal solutions to optimization problems, such as the genetic algorithm (GA) [22; 23], the artificial bee colony algorithm (ABC) [24], and the particle swarm optimization (PSO) [25]. In contrast to various evolutionary techniques, PSO is regarded as one of the best-accepted techniques that are cheap in time consumption and simple for implementation. However, the classical PSO algorithm has the defects of poor local search ability and low search efficiency. To improve the performance of PSO, an adaptive PSO algorithm based on an evolutionary factor has been proposed by [PERSON] et al. [26]. It could adaptively control the PSO's parameters, including the inertia weight and other parameters. Moreover, the author developed a novel switching delayed PSO (SDPSO) algorithm based on the adaptive switching strategy and the delayed information [27]. It dramatically improves the search efficiency and convergence speed of the PSO algorithm. However, the conclusions were obtained only through five simple unconstrained functions. The application of SDPSO in practical constrained engineering problems has not been investigated. An industrial high-pressure turbine (HPT) sealing disk was initially designed with seventy-five circular vent holes, where severe stress concentration occurs. To handle the stress concentration and reduce the maximum von Mises stress of the initial circular vent holes, this paper attempts to redesign and optimize the shape of the vent holes. Different from the existing studies, an effective integrated design optimization method is developed. The main contribution of this paper is: (1) developing an effective integrated design optimization method for the shape design of vent holes of the HPT sealing disk to reduce the maximum von Mises stress; (2) optimizing and comparing different shapes of vent holes, and analyzing and finding out the best design scheme to meet the needs of industrial design; and (3) investigating the practicality of SDPSO in engineering optimization problems with constraints.
# THz Data Analysis and Self-Organizing Map (SOM) for the Quality Assessment of Hazelnuts
## 1 Introduction
Since terahertz radiation excites rotational and roto/vibrational transitions, polar liquids such as water are sensitive to these frequencies, exhibiting both strong absorption and reflection. So, while this allows us to determine the amount of moisture in food or water in biological tissues, including leaves and plants, it also severely limits deep penetration [26]. Some chemical compounds have an absorption spectrum in the THz region [27]; this detail leads to the detection of all those chemical substances present in foods that show a significant fingerprint in the THz band. Moreover, at these frequencies, dielectric materials such as plastic and paper are transparent whereby the contents of a package can be easily analyzed using this radiation [28]. Moreover, it worth noting that in recent years, interest in neural networks applied to the field of agri-food field has grown. Indeed, artificial neural networks (ANNs) can be used to inspect the quality of food products [29; 30; 31; 32; 33; 34; 35; 36; 37], like wine and beer [38; 39; 40; 41; 42; 43; 44; 45; 46; 47; 48]. In an artificial neural network, the learning process can be either supervised or unsupervised. In the first case, supervised learning is trained to produce desired outputs in response to sampled inputs. In unsupervised networks, the search for a logical classification of input data is left to the network itself. This is the case of self-organizing maps (SOMs), whose most common SOM model is the one proposed by the Finnish researcher [PERSON] in 1982 [49; 50]. The main fields of interest of SOMs include pattern recognition, robotics, telecommunications and medical applications [51; 52; 53]. This type of neural network is widely used as a clustering tool by detecting the most representative patterns in the dataset [54]. In this study, millimeter wave measurements to select healthy, empty and rotten hazelnuts samples have been made by using an experimental setup designed to perform measures in transmission configuration. Two different data analysis techniques have been used for the sorting of hazelnut samples: one relied on a statistical-based algorithm, and another one is more complex and based on the use of an unsupervised neural network.