Search results for: label propagation

Authors: Kunal Shah, Swati Patel

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Many real world problems involve data which can be considered as multi-label data streams. Efficient methods exist for multi-label classification in non streaming scenarios. However, learning in evolving streaming scenarios is more challenging, as the learners must be able to adapt to change using limited time and memory. Classification is used to predict class of unseen instance as accurate as possible. Multi label classification is a variant of single label classification where set of labels associated with single instance. Multi label classification is used by modern applications, such as text classification, functional genomics, image classification, music categorization etc. This paper introduces the task of multi-label classification, methods for multi-label classification and evolution measure for multi-label classification. Also, comparative analysis of multi label classification methods on the basis of theoretical study, and then on the basis of simulation was done on various data sets.

Keywords: binary relevance, concept drift, data stream mining, MLSC, multiple window with buffer

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Authors: Qingsong Xiong, Cheng Yuan, Qingzhao Kong, Haibei Xiong

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Deep-learning-driven approaches based on vibration responses have attracted larger attention in rapid structural condition assessment while obtaining sufficient measured training data with corresponding labels is relevantly costly and even inaccessible in practical engineering. This study proposes an integrated label propagation network for structural condition assessment, which is able to diffuse the labels from continuously-generating measurements by intact structure to those of missing labels of damage scenarios. The integrated network is embedded with damage-sensitive features extraction by deep autoencoder and pseudo-labels propagation by optimized fuzzy clustering, the architecture and mechanism which are elaborated. With a sophisticated network design and specified strategies for improving performance, the present network achieves to extends the superiority of self-supervised representation learning, unsupervised fuzzy clustering and supervised classification algorithms into an integration aiming at assessing damage conditions. Both numerical simulations and full-scale laboratory shaking table tests of a two-story building structure were conducted to validate its capability of detecting post-earthquake damage. The identifying accuracy of a present network was 0.95 in numerical validations and an average 0.86 in laboratory case studies, respectively. It should be noted that the whole training procedure of all involved models in the network stringently doesn’t rely upon any labeled data of damage scenarios but only several samples of intact structure, which indicates a significant superiority in model adaptability and feasible applicability in practice.

Keywords: autoencoder, condition assessment, fuzzy clustering, label propagation

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Authors: Ziad Abdallah, Mohamad Oueidat, Ali El-Zaart

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Image Multi-label Classification (IMC) assigns a label or a set of labels to an image. The big demand for image annotation and archiving in the web attracts the researchers to develop many algorithms for this application domain. The existing techniques for IMC have two drawbacks: The description of the elementary characteristics from the image and the correlation between labels are not taken into account. In this paper, we present an algorithm (MIML-HOGLPP), which simultaneously handles these limitations. The algorithm uses the histogram of gradients as feature descriptor. It applies the Label Priority Power-set as multi-label transformation to solve the problem of label correlation. The experiment shows that the results of MIML-HOGLPP are better in terms of some of the evaluation metrics comparing with the two existing techniques.

Keywords: data mining, information retrieval system, multi-label, problem transformation, histogram of gradients

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Authors: Vladimir Kulyukin, Tanwir Zaman, Sarat Kiran Andhavarapu

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Research on nutrition label use identifies four factors that impede comprehension and retention of nutrition information by consumers: label’s location on the package, presentation of information within the label, label’s surface size, and surrounding visual clutter. In this paper, a system is presented that makes nutrition label use more effective for nutrition information comprehension and retention. The system’s front end is a smartphone application. The system’s back end is a four node Linux cluster for image recognition and data storage. Image frames captured on the smartphone are sent to the back end for skewed or aligned barcode recognition. When barcodes are recognized, corresponding nutrition labels are retrieved from a cloud database and presented to the user on the smartphone’s touchscreen. Each displayed nutrition label is positioned centrally on the touchscreen with no surrounding visual clutter. Wikipedia links to important nutrition terms are embedded to improve comprehension and retention of nutrition information. Standard touch gestures (e.g., zoom in/out) available on mainstream smartphones are used to manipulate the label’s surface size. The nutrition label database currently includes 200,000 nutrition labels compiled from public web sites by a custom crawler. Stress test experiments with the node cluster are presented. Implications for proactive nutrition management and food policy are discussed.

Keywords: mobile computing, cloud computing, nutrition label use, nutrition management, barcode scanning

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Authors: Pengchao Wei, Xiangzhong Fang

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Noise is ubiquitous in this world. Denoising is an essential technology, especially in image semantic segmentation, where noises are generally categorized into two main types i.e. feature noise and label noise. The main focus of this paper is aiming at modeling label noise, investigating the behaviors of different types of label noise on image semantic segmentation tasks using K-Nearest-Neighbor and Convolutional Neural Network classifier. The performance without label noise and with is evaluated and illustrated in this paper. In addition to that, the influence of feature noise on the image semantic segmentation task is researched as well and a feature noise reduction method is applied to mitigate its influence in the learning procedure.

Keywords: convolutional neural network, denoising, feature noise, image semantic segmentation, k-nearest-neighbor, label noise

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Authors: Barby Jennette A. Florano

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Dietary intake has been associated with the health and wellbeing of adults, and lifestyle related diseases. The aim of this study was to investigate whether nutrition knowledge, food label use, and food preference are associated with the dietary intake in a sample of San Jose Del Monte City, Bulacan (SJDM) adults. A sample of 148 adults, with a mean age of 20 years, completed a validated questionnaire related to their demographic, dietary intake, nutrition knowledge, food label use and food preference. Data were analyzed using Pearson correlation and there was no association between dietary intake and nutrition knowledge. However, there were positive relationships between dietary intake and food label use (r=0.1276, p<0.10), and dietary intake and food preference (r=0.1070, p<0.10). SJDM adults who use food label and have extensive food preference had better diet quality. This finding magnifies the role of nutrition education as a potential tool in health campaigns to promote healthy eating patterns and reading food labels among students and adults. Results of this study can give information for the design of future nutrition education intervention studies to assess the efficacy of nutrition knowledge and food label use among a similar sample population.

Keywords: dietary intake, nutrition knowledge, food preference, food label use

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Authors: Noboru Abe, Yoshinori Amai, Toshinori Nakatake, Sumio Masuda, Kazuaki Yamaguchi

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We consider the problem of placing labels of the points on a plane. For each point, its position, the size of its label and a priority are given. Moreover, several candidates of its label positions are prespecified, and each of such label positions is assigned a priority. The objective of our problem is to maximize the total sum of priorities of placed labels and their points. By refining a labeling algorithm that can use these priorities, we propose a new heuristic algorithm which is more suitable for treating the assigned priorities.

Keywords: map labeling, greedy algorithm, heuristic algorithm, priority

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Authors: Azeddine El-Hassouny, Chandrashekhar Meshram, Geraldin Nanfack

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In recent years, learning from data with noisy labels (Label Noise) has been a major concern in supervised learning. This problem has become even more worrying in Deep Learning, where the generalization capabilities have been questioned lately. Indeed, deep learning requires a large amount of data that is generally collected by search engines, which frequently return data with unreliable labels. In this paper, we investigate the Label Noise in Deep Learning using variational inference. Our contributions are : (1) exploiting Label Noise concept where the true labels are learnt using reparameterization variational inference, while observed labels are learnt discriminatively. (2) the noise transition matrix is learnt during the training without any particular process, neither heuristic nor preliminary phases. The theoretical results shows how true label distribution can be learned by variational inference in any discriminate neural network, and the effectiveness of our approach is proved in several target datasets, such as MNIST and CIFAR32.

Keywords: label noise, deep learning, discrete latent variable, variational inference, MNIST, CIFAR32

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Authors: Po-Jen Chen, Jian-Jiun Ding, Hung-Wei Hsu, Chien-Yao Wang, Jia-Ching Wang

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A more accurate scene classification algorithm using label relations and the hierarchy neural network was developed in this work. In many classification algorithms, it is assumed that the labels are mutually exclusive. This assumption is true in some specific problems, however, for scene classification, the assumption is not reasonable. Because there are a variety of objects with a photo image, it is more practical to assign multiple labels for an image. In this paper, two label relations, which are exclusive relation and hierarchical relation, were adopted in the classification process to achieve more accurate multiple label classification results. Moreover, the hierarchy neural network (hierarchy NN) is applied to classify the image and the directed acyclic graph structure is used for predicting a more reasonable result which obey exclusive and hierarchical relations. Simulations show that, with these techniques, a much more accurate scene classification result can be achieved.

Keywords: convolutional neural network, label relation, hierarchy neural network, scene classification

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Authors: Seon Soon Choi

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It is necessary to predict a fatigue crack propagation life for estimation of structural integrity. Because of an uncertainty and a randomness of a structural behavior, it is also required to analyze stochastic characteristics of the fatigue crack propagation life at a specified fatigue crack size. The essential purpose of this study is to present the good probability distribution fit for the fatigue crack propagation life at a specified fatigue crack size in magnesium alloys under various fatigue load ratio conditions. To investigate a stochastic crack growth behavior, fatigue crack propagation experiments are performed in laboratory air under several conditions of fatigue load ratio using AZ31. By Anderson-Darling test, a goodness-of-fit test for probability distribution of the fatigue crack propagation life is performed and the good probability distribution fit for the fatigue crack propagation life is presented. The effect of load ratio on variability of fatigue crack propagation life is also investigated.

Keywords: fatigue crack propagation life, load ratio, magnesium alloys, probability distribution

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Authors: Seon Soon Choi

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The principal purpose of this paper is to find the influence of maximum fatigue load on the probabilistic aspect of fatigue crack propagation life at a specified grown crack in magnesium alloys. The experiments of fatigue crack propagation are carried out in laboratory air under different conditions of the maximum fatigue loads to obtain the fatigue crack propagation data for the statistical analysis. In order to analyze the probabilistic aspect of fatigue crack propagation life, the goodness-of fit test for probability distribution of the fatigue crack propagation life at a specified grown crack is implemented through Anderson-Darling test. The good probability distribution of the fatigue crack propagation life is also verified under the conditions of the maximum fatigue loads.

Keywords: fatigue crack propagation life, magnesium alloys, maximum fatigue load, probability

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Authors: Addin Osman, Anwar Ali Yahya, Mohammed Basit Kamal

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Datasets or collections are becoming important assets by themselves and now they can be accepted as a primary intellectual output of a research. The quality and usage of the datasets depend mainly on the context under which they have been collected, processed, analyzed, validated, and interpreted. This paper aims to present a collection of program educational objectives mapped to student’s outcomes collected from self-study reports prepared by 32 engineering programs accredited by ABET. The manual mapping (classification) of this data is a notoriously tedious, time consuming process. In addition, it requires experts in the area, which are mostly not available. It has been shown the operational settings under which the collection has been produced. The collection has been cleansed, preprocessed, some features have been selected and preliminary exploratory data analysis has been performed so as to illustrate the properties and usefulness of the collection. At the end, the collection has been benchmarked using nine of the most widely used supervised multiclass classification techniques (Binary Relevance, Label Powerset, Classifier Chains, Pruned Sets, Random k-label sets, Ensemble of Classifier Chains, Ensemble of Pruned Sets, Multi-Label k-Nearest Neighbors and Back-Propagation Multi-Label Learning). The techniques have been compared to each other using five well-known measurements (Accuracy, Hamming Loss, Micro-F, Macro-F, and Macro-F). The Ensemble of Classifier Chains and Ensemble of Pruned Sets have achieved encouraging performance compared to other experimented multi-label classification methods. The Classifier Chains method has shown the worst performance. To recap, the benchmark has achieved promising results by utilizing preliminary exploratory data analysis performed on the collection, proposing new trends for research and providing a baseline for future studies.

Keywords: ABET, accreditation, benchmark collection, machine learning, program educational objectives, student outcomes, supervised multi-class classification, text mining

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Authors: Gorkem Algan, Ilkay Ulusoy, Saban Gonul, Banu Turgut, Berker Bakbak

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Computer vision systems recently made a big leap thanks to deep neural networks. However, these systems require correctly labeled large datasets in order to be trained properly, which is very difficult to obtain for medical applications. Two main reasons for label noise in medical applications are the high complexity of the data and conflicting opinions of experts. Moreover, medical imaging datasets are commonly tiny, which makes each data very important in learning. As a result, if not handled properly, label noise significantly degrades the performance. Therefore, a label-noise-robust learning algorithm that makes use of the meta-learning paradigm is proposed in this article. The proposed solution is tested on retinopathy of prematurity (ROP) dataset with a very high label noise of 68%. Results show that the proposed algorithm significantly improves the classification algorithm's performance in the presence of noisy labels.

Keywords: deep learning, label noise, robust learning, meta-learning, retinopathy of prematurity

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Authors: A. Keshavarz

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A physical model for guiding the wave in photorefractive media is studied. Propagation of cos-Gaussian beam as the special cases of sinusoidal-Gaussian beams in photorefractive crystal is simulated numerically by the Crank-Nicolson method in one dimension. Results show that the beam profile deforms as the energy transfers from the center to the tails under propagation. This simulation approach is of significant interest for application in optical telecommunication. The results are presented graphically and discussed.

Keywords: beam propagation, cos-Gaussian beam, numerical simulation, photorefractive crystal

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Authors: Pooja Khanal, Huaming Zhang

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Labeling of issues/bugs, also known as bug classification, plays a vital role in software engineering. Some known labels/classes of bugs are 'User Interface', 'Security', and 'API'. Most of the time, when a reporter reports a bug, they try to assign some predefined label to it. Those issues are reported for a project, and each project is a repository in GitHub/GitLab, which contains multiple issues. There are many software project repositories -ranging from individual projects to commercial projects. The labels assigned for different repositories may be dependent on various factors like human instinct, generalization of labels, label assignment policy followed by the reporter, etc. While the reporter of the issue may instinctively give that issue a label, another person reporting the same issue may label it differently. This way, it is not known mathematically if a label in one repository is similar or different to the label in another repository. Hence, the primary goal of this research is to find the semantic differences between bug labeling of different repositories via machine learning. Independent optimal classifiers for individual repositories are built first using the text features from the reported issues. The optimal classifiers may include a combination of multiple classifiers stacked together. Then, those classifiers are used to cross-test other repositories which leads the result to be deduced mathematically. The produce of this ongoing research includes a formalized open-source GitHub issues database that is used to deduce the similarity of the labels pertaining to the different repositories.

Keywords: bug classification, bug labels, GitHub issues, semantic differences

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Authors: Teles de Sales Bezerra, Saulo Aislan da Silva Eleuterio, José Anderson Rodrigues de Souza, Jeronimo Silva Rocha

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Propagation in radio frequency is a constant concern in the application of Wireless Sensor Networks (WSN), the behavior of an environment determines how good the quality of signal reception. The objective of this paper is to analyze the behavior of a WSN in an environment for agriculture where environmental variables are present and correlate the capture of values received signal strength (RSSI) with a propagation model.

Keywords: propagation, WSN, agriculture, quality

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Authors: Morteza Raki, Abolghasem Zabihollah, Omid Askari

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Cantilever beam is a simplified sample of a lot of mechanical components used in a wide range of applications, including many industries such as gas turbine blade. Due to the nature of the operating conditions, beams are subject to variety of damages especially crack propagates. Crack propagation may lead to catastrophic failure during operation. Therefore, online detection of crack presence and its propagation is very important and may reduce possible significant cost of the whole system failure. This paper aims to investigate the effect of cracks presence and crack propagation on one end fixed beam`s vibration. A finite element model will be developed for the blade in which the modal response of the structure with and without crack will be studied. 

Keywords: blade, crack propagation, health monitoring, modal analysis

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Authors: Gabriela Iordachescu, Mariana Cretu Stuparu, Mirela Praisler, Camelia Busila, Doina Voinescu, Camelia Vizireanu

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The aim of the study was to evaluate the consumers’ degree of confidence in food labeling, how they use and understand the label and respectively food labeling elements. The label is a bridge between producers, suppliers, and consumers. It has to offer enough information in terms of public health and food safety, statement of ingredients, nutritional information, warnings and advisory statements, producing date and shelf-life, instructions for storage and preparation (if required). The survey was conducted on 500 consumers group in Romania, aged 15+, males and females, from urban and rural areas and with different graduation levels. The questionnaire was distributed face to face and online. It had single or multiple choices questions and label images for the efficiency and best understanding of the question. The law 1169/2011 applied to food products from 13 of December 2016 improved and adapted the requirements for labeling in a clear manner. The questions were divided on following topics: interest and general trust in labeling, use and understanding of label elements, understanding of the ingredient list and safety information, nutrition information, advisory statements, serving sizes, best before/use by meanings, intelligent labeling, and demographic data. Three choice selection exercises were also included. In this case, the consumers had to choose between two similar products and evaluate which label element is most important in product choice. The data were analysed using MINITAB 17 and PCA analysis. Most of the respondents trust the food label, taking into account some elements especially when they buy the first time the product. They usually check the sugar content and type of sugar, saturated fat and use the mandatory label elements and nutrition information panel. Also, the consumers pay attention to advisory statements, especially if one of the items is relevant to them or the family. Intelligent labeling is a challenging option. In addition, the paper underlines that the consumer is more careful and selective with the food consumption and the label is the main helper for these.

Keywords: consumers, food safety information, labeling, labeling nutritional information

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Authors: Purva Joshi, Rohit Thanki, Omar Hanif

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Unmanned aerial vehicles (UAVs) are becoming increasingly important in various industrial applications and sectors. Nowadays, a multi UAV network is used for specific types of communication (e.g., military) and monitoring purposes. Therefore, it is critical to reducing propagation delay during communication between UAVs, which is essential in a multi UAV network. This paper presents how the propagation delay between the base station (BS) and the UAVs is reduced using a searching algorithm. Furthermore, the iterative-based K-nearest neighbor (k-NN) algorithm and Travelling Salesmen Problem (TSP) algorthm were utilized to optimize the distance between BS and individual UAV to overcome the problem of propagation delay in multi UAV networks. The simulation results show that this proposed method reduced complexity, improved reliability, and reduced propagation delay in multi UAV networks.

Keywords: multi UAV network, optimal distance, propagation delay, K - nearest neighbor, traveling salesmen problem

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Authors: A. Keshavarz, Z. Roosta

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In this paper, propagation of cos-Gaussian beam in strongly nonlocal nonlinear media has been stimulated by using paraxial group transformation. At first, cos-Gaussian beam, nonlocal nonlinear media, critical power, transfer matrix, and paraxial group transformation are introduced. Then, the propagation of the cos-Gaussian beam in strongly nonlocal nonlinear media is simulated. Results show that beam propagation has periodic structure during self-focusing effect in this case. However, this simple method can be used for investigation of propagation of kinds of beams in ABCD optical media.

Keywords: paraxial group transformation, nonlocal nonlinear media, cos-Gaussian beam, ABCD law

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Authors: R. Srinivas, K. V. Ramana

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This paper presents a novel method called VESTAL to label vertebrae and inter vertebral discs. Each vertebra has certain statistical features properties. To label vertebrae and discs, a new equation to model the path of spinal cord is derived using statistical properties of the spinal canal. VESTAL uses this equation for labeling vertebrae and discs. For each vertebrae and inter vertebral discs both posterior, interior width, height are measured. The calculated values are compared with real values which are measured using venires calipers and the comparison produced 95% efficiency and accurate results. The VESTAL is applied on 50 patients 350 MR images and obtained 100% accuracy in labeling.

Keywords: spine, vertebrae, inter vertebral disc, labeling, statistics, texture, disc

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Authors: Tao Qu, Chandra Prakash, Vikas Tomar

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The interfaces between organic and inorganic phases in natural materials have been shown to be a key factor contributing to their high performance. This work analyzes crack propagation in a 2-ply laminate subjected to uniaxial tensile mode-I crack propagation loading that has laminate properties derived based on biological material constituents (marine exoskeleton- chitin and calcite). Interfaces in such laminates are explicitly modeled based on earlier molecular simulations performed by authors. Extended finite element method and cohesive zone modeling based simulations coupled with theoretical analysis are used to analyze crack propagation. Analyses explicitly quantify the effect that interface mechanical property variation has on the delamination as well as the transverse crack propagation in examined 2-ply laminates.

Keywords: chitin, composites, interfaces, fracture

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Authors: Zoran Jovanovic, Zoran Masonicic, S. Dragutinovic, Z. Sakota

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In this paper, results concerning flame propagation of various fuels in a particular combustion chamber with four tilted valves were elucidated. Flame propagation was represented by the evolution of spatial distribution of temperature in various cut-planes within combustion chamber while the flame front location was determined by dint of zones with maximum temperature gradient. The results presented are only a small part of broader on-going scrutinizing activity in the field of multidimensional modeling of reactive flows in combustion chambers with complicated geometries encompassing various models of turbulence, different fuels and combustion models. In the case of turbulence two different models were applied i.e. standard k-ε model of turbulence and k-ξ-f model of turbulence. In this paper flame propagation results were analyzed and presented for two different hydrocarbon fuels, such as CH4 and C8H18. In the case of combustion all differences ensuing from different turbulence models, obvious for non-reactive flows are annihilated entirely. Namely the interplay between fluid flow pattern and flame propagation is invariant as regards turbulence models and fuels applied. Namely the interplay between fluid flow pattern and flame propagation is entirely invariant as regards fuel variation indicating that the flame propagation through unburned mixture of CH4 and C8H18 fuels is not chemically controlled.

Keywords: automotive flows, flame propagation, combustion modelling, CNG

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Authors: Fatima El Kandoussi, Lamiae El Hdiddioui, Mustapha Bouragba

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The woodwork of thuja in Essaouira is one of the main crafts in Morocco. Certainly, marquetry reflects both cultural and artistic identity of the city, considering the talent and ancestral knowledge of craftsman working in marquetry. Yet, the production units encounter a considerable number of difficulties among which insufficiencies within marketing practices. Consequently, it is obvious that major improvements are needed, and supportive solutions must be provided in order to improve the Essaouira’s marquetry, as a symbol of the entire province. Thus, the establishment of Thuja Label is a necessary measure that would be the key to ensuring sustainability of this vital craft. The main purpose of this paper is to study marketing practices’ current state of the production units in the marquetry of Essaouira, therefore to recommend remedial actions likely to raise them up to the required functional level.

Keywords: craft, marketing practices, marquetry, thuja label

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Authors: Fathi Alwafie

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In this paper we present the simulation of the propagation characteristics of the picocellular propagation channel environment. The first aim has been to find a correct description of the environment for received wave. The result of the first investigations is that the environment of the indoor wave significantly changes as we change the electric parameters of material constructions. A modified 3D ray tracing image method tool has been utilized for the coverage prediction. A detailed analysis of the dependence of the indoor wave on the wide-band characteristics of the channel: Root Mean Square (RMS) delay spread characteristics and mean excess delay, is also investigated.

Keywords: propagation, ray tracing, network, mobile computing

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Authors: Abdulatif Abdusalam, Mohamed Shaban

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In this paper, we consider the nonlinear pulse propagation through a nonuniform birefringent fiber Bragg grating (FBG) whose index modulation depth varies along the propagation direction. Here, the pulse propagation is governed by the nonlinear birefringent coupled mode (NLBCM) equations. To form the Bragg soliton outside the photonic bandgap (PBG), the NLBCM equations are reduced to the well known NLS type equation by multiple scale analysis. As we consider the pulse propagation in a nonuniform FBG, the pulse propagation outside the PBG is governed by inhomogeneous NLS (INLS) rather than NLS. We, then, discuss the formation of soliton in the FBG known as Bragg soliton whose central frequency lies outside but close to the PBG of the grating structure. Further, we discuss Bragg soliton compression due to a delicate balance between the SPM and the varying grating induced dispersion. In addition, Bragg soliton collision, Bragg soliton switching and possible logic gates have also been discussed.

Keywords: Bragg grating, non uniform fiber, non linear pulse

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Authors: Ding Yu, Ge Yang, Wang Hong-Tao

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Aiming at the detonation performance and detonation wave propagation distance of liquid fuel detonation engine, the kerosene/oxygen-enriched air mixture is chosen as the research object; its detonation initiation and detonation wave propagation process by mild energy input are numerically studied by using Euler-Lagrange method in the present study. The effects of a semicircular obstacle, rectangular obstacle, and triangular obstacle on the detonation characteristic parameters in the detonation tube are compared and analyzed, and the effect of the angle between obstacle and flame propagation direction on flame propagation characteristics and detonation process when the blocking ratio is constant are studied. The results show that the flame propagation velocity decreases with the increase of the angle in the range of 0-90°, and when the angle is 0° which corresponds to the semicircle obstacle gets the highest detonation wave propagation velocity. With the increase of the angle in the range of 0-90°, DDT (Deflagration to detonation transition) distance decreases first and then increases.

Keywords: deflagration to detonation transition, numerical simulation, obstacle structure, turbulent flame

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Authors: S. Levitsky, R. Bergman

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Fluid rheology may have essential impact on sound propagation in a liquid-filled pipe, especially, in a low frequency range. Rheological parameters of liquid are temperature-sensitive, which ultimately results in a temperature dependence of the wave speed and attenuation in the waveguide. The study is devoted to modeling of this effect at sound propagation in an elastic pipe with polymeric liquid, described by generalized Maxwell model with non-zero high-frequency viscosity. It is assumed that relaxation spectrum is distributed according to the Spriggs law; temperature impact on the liquid rheology is described on the basis of the temperature-superposition principle and activation theory. The dispersion equation for the waveguide, considered as a thin-walled tube with polymeric solution, is obtained within a quasi-one-dimensional formulation. Results of the study illustrate the influence of temperature on sound propagation in the system.

Keywords: elastic tube, sound propagation, temperature effect, viscoelastic liquid

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Authors: Yuan Xu, Xun Liang, Meina Zhang

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The rise and attenuation of the public opinion broadcast of an emergent accident, in the social network, has a close relationship with the dynamic development of its subevents cluster. In this article, we take Tianjin Port explosion's subevents as an example to research the dynamic propagation discipline of Internet public opinion in a sudden accident, and analyze the overall structure of dynamic propagation to propose four different routes for subevents clusters propagation. We also generate network diagrams for the dynamic public opinion propagation, analyze each propagation type specifically. Based on this, suggestions on the supervision and guidance of Internet public opinion broadcast can be made.

Keywords: network dynamic transmission modes, emergent subevents clusters, Tianjin Port explosion, public opinion supervision

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Authors: Bartholomew Badar

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An NFT is a digital certificate with rights to own an asset, including various valuable digital goods such as art pieces, music items, collectibles, etc. The market for NFTs started developing in 2017 and has lately seen increased growth as crypto-currencies and the blockchain market continue to gain popularity. This study aims to understand potential uses for NFTs concerning the music industry and record labels. Independent artists struggle to distribute and sell their music without the help of a record label. The NFT marketplace could be a great tool to eliminate this problem. The research objective is to identify possibilities for independent artists to own their music rights and share value with an audience. We see a trend of new-school music artists trying to enter the music NFT market by creating visualizers, beats, cover art, etc. To analyze various existing music NFT assets and determine whether or not independent artists could monetize their music without a record label is the main focus of this scholarly paper.

Keywords: blockchain, crypto-currency, music, artist, NFT

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