bluuebunny/crossref_metadata_2025 huggingface dataset:
[Retracted] Design of Chinese Grammar Recognition and Error Correction Model Based on the Deep Neural Network
Authors: Qiao Yuhan , Liang Lin
Published: August 2022

In order to further improve the performance of the automatic grammar error detection system, a new Chinese grammar recognition and correction model is proposed in this paper. Based on the transformer attention mechanism, the bias matrix of Gaussian distribution is added to improve the attention of the model to local text and strengthen the information extraction of wrong words and surrounding words in the wrong text. In addition, the ON_LSTM model is used to extract grammatical information from the special grammatical structure of error text. The experimental results show that the two methods can effectively improve the accuracy and recall rate, and the fused model achieves the highest F1 value. Finally, the Chinese text error correction system is designed to expand the application scope of the model, which helps to reduce the human cost in language learning.
The Efficacy and Cost-Effectiveness of Umeclidinium/Vilanterol versus Tiotropium in Symptomatic Patients with Chronic Obstructive Pulmonary Disease
Authors: Gong Yinhua , Lin Chen , Jin Yifeng , Chen Rong
Published: August 2022

Background. Both long-acting muscarinic antagonists (LAMAs) and long-acting β2-agonists (LABAs) are widely used in the treatment of chronic obstructive pulmonary disease (COPD). A novel LAMA/LABA combination of umeclidinium/vilanterol (UMEC/VI; 62.5 μg/25 μg) is approved for chronic obstructive pulmonary disease (COPD) treatment. Objective. This study aimed to assess the efficacy and cost-effectiveness of UMEC/VI versus tiotropium (TIO) 18 μg in symptomatic patients with COPD from the perspective of the Chinese National Healthcare System. Methods. A simple analysis included three studies in the meta-analysis that compared UMEC/VI with TIO. A Markov model was developed to estimate the cost-effectiveness of UMEC/VI compared with TIO treatment in symptomatic patients with COPD. First, utilities, clinical efficacy, and adverse events obtained from the literature were utilized as model inputs. Costs were from Chinese average data, including local data. Costs were expressed in dollars based on 2020 prices. Then, the model outputs including drug costs, other medical costs, and total costs, and quality-adjusted life years (QALYs) were estimated. Costs and outcomes were discounted at a 5% annual rate. Furthermore, incremental cost-effective ratios (ICERs) were analyzed. Finally, the influences of changing parameters on the uncertainty of the results were assessed by means of one-way and probabilistic sensitivity analyses. Results. This study revealed that UMEC/VI treatment had a higher rate of clinical efficacy in comparison with TIO, and the differences in the rate of adverse events between the two treatments were not significant. The results indicated that UMEC/VI was superior to TIO, which provided an increase in QALYs (0.002) and a total cost savings of $765.67 per patient over 3 years. In the base case, the ICER of UMEC/VI is -$397468.04/QALY compared with TIO, suggesting that UMEC/VI may be considered a dominant option over TIO. According to the Chinese medical system, the probability of UMEC/VI being cost-effective was 61.6% at a willingness-to-pay (WTP) of $31554/QALY. Sensitivity analyses confirmed that the results were robust. Conclusion. UMEC/VI could be considered a cost-effective treatment compared with TIO in symptomatic COPD patients from the Chinese National Healthcare System perspective. These results may help decision-makers in China when making judgements on which treatments to administer.
Deep Global-Local Gazing: Including Global Scene Properties in Local Saliency Computation
Authors: Zabihi Samad , Yazdi Mehran , Mansoori Eghbal
Published: August 2022

Visual saliency models imitate the attentive mechanism of the human visual system (HVS) to detect the objects that stand out from their neighbors in the scene. Some biological phenomena in HVS, such as contextual cueing effects, suggest that the contextual information of the whole scene does guide the attentive mechanism. The saliency value of each image patch is influenced by its visual (local) features as well as the contextual information of the whole scene. Modern saliency models are based on deep convolutional neural networks. Because the convolutional operators operate locally and use weight sharing, such networks inherently have difficulty capturing global and location-dependent features. In addition, these models calculate the saliency value pixel-wise using local features. Therefore, it is necessary to provide global features along with local features. In this regard, we propose two approaches for capturing the contextual information from the scene. In our first method, we introduce a shift-variant fully connected component to capture global and location-dependent information. Instead of using the native CNN of our base model, in our second method, we use a VGGNet to capture the global and context information of the scene. To show the effectiveness of our methods, we use them to extend the SAM-ResNet saliency model. To evaluate our proposed approaches, four challenging saliency benchmark datasets were used. The experimental results showed that our methods could outperform the existing state-of-the-art saliency prediction models.
Application of Speech Interaction System Model Based on Semantic Search in English MOOC Teaching System
Authors: Pan Bingbing , Zhou Yanna
Published: August 2022

In order to improve the effect of English MOOC teaching, this study combines the semantic search algorithm to construct an English MOOC teaching system to promote the interactive effect of English teaching. Moreover, this study analyzes a DOA estimation method based on sparse iterative covariance and an improved method, and no prior knowledge of noise is required to use this method in noisy data scenarios. In addition, this study constructs an English interactive teaching system based on semantic search. Finally, this study uses the course resources of the MOOC platform to teach students, perform organizational collaboration, and answer the questions. The research shows that the speech interaction system model based on semantic search proposed in this study has a better application effect in the English MOOC teaching system.
A Study on the Evaluation of the Innovation Efficiency of Star Hotel Services Based on the DEA-Malmquist Index
Authors: Yao Xianlin , Hong Juan , Zeng Lixiang
Published: August 2022

Based on the panel data of star-rated hotels in China from 2015 to 2021, the following conclusions were drawn by using the DEA-Malmquist index method to investigate the efficiency of service innovation of star-rated hotels in China and to analyze the factors that influenced the change in the efficiency of star-rated hotels in China [1]. The service innovation efficiency of high-star hotels has a high sensitivity to changes in the external environment, while low-star hotels show a relatively resilient life under the unfavorable external circumstance [2]. Technological progress is an important reason for the promotion of service innovation efficiency, especially the key reason for the improvement of service innovation efficiency of high-star hotels [3]. The expansion of enterprise-scale has a more obvious inhibiting effect on the improvement of service innovation efficiency of low-star hotels [4]. After the epidemic, pure technical efficiency can obviously promote the service innovation efficiency.
Edge Computing Server Placement Strategy Based on SPEA2 in Power Internet of Things
Authors: Lu Yongling , Wang Zhen , Hu Chengbo , Liu Ziquan , Zhu Xueqiong
Published: August 2022

In order to meet the edge services placement demand for multiobjective optimization of Power Internet of Things, an edge services placement strategy based on an improved strength Pareto evolutionary algorithm (SPEA2) is proposed in this paper. Firstly, we model the delay, resource utilization, and energy consumption. Then, a multiobjective optimization is proposed. Finally, an enhanced genetic algorithm is used to derive the decision candidate set. Moreover, the optimal solution in the candidate set is selected to be utilized in the iteration of the multicriteria decision and the superior-inferior solution distance method. Numerical results and analysis show that the proposed strategy is more effective in reducing system delay, improving resource utilization, and saving energy consumption than the other two benchmark algorithms.
Intelligent Development of Enterprise Management Innovation Based on Artificial Neural Network
Authors: Wu Jintao , Ding Xinlong
Published: August 2022

Artificial intelligence technology is gradually entering all aspects of our lives while also promoting the development of various fields. Artificial intelligence can also solve problems that could not be solved by computing before. This paper combines artificial intelligence and network function virtualization, two very advanced and popular technologies in modern society, and uses neural networks to solve and develop the service chain problem in network function virtualization. The simulation shows that all algorithms almost decrease linearly with the change of VNR. This decrease means that there is no noise. The optimal mapping of each VNE problem can be achieved within the scope of the existing solutions, and the heuristic method is to try to find possible mappings. In terms of enterprise management innovation, this article points out the need to strengthen in-depth cooperation and exchanges between universities and enterprises. At the same time, the government, as a third party in cooperation, should play an active leadership role and an intermediary coordination role. In terms of innovation management cooperation, the establishment and improvement of government plans and policy support mechanisms are important external driving factors.
UHPLC-MS/MS-Based Metabolomics and Clinical Phenotypes Analysis Reveal Broad-Scale Perturbations in Early Pregnancy Related to Gestational Diabetes Mellitus
Authors: Hu Ting , An Zhuoling , Li Han , Liu Yanping , Xia Liangyu , Qiu Ling , Yao Aimin , Ma Liangkun , Liu Lihong
Published: August 2022

Gestational diabetes mellitus (GDM) is the most common metabolic disturbance during pregnancy, with adverse effects on both mother and fetus. The establishment of early diagnosis and risk assessment model is of great significance for preventing and reducing adverse outcomes of GDM. In this study, the broad-scale perturbations related to GDM were explored through the integration analysis of metabolic and clinical phenotypes. Maternal serum samples from the first trimester were collected for targeted metabolomics analysis by using ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Statistical analysis was conducted based on the levels of the 184 metabolites and 76 clinical indicators from GDM women (

n

 =60) and matched healthy controls (

n

 =90). Metabolomics analysis revealed the down-regulation of fatty acid oxidation in the first trimester of GDM women, which was supposed to be related to the low serum level of dehydroepiandrosterone.While the significantly altered clinical phenotypes were mainly related to the increased risk of cardiovascular disease, abnormal iron metabolism, and inflammation. A phenotype panel established from the significantly changed serum indicators can be used for the early prediction of GDM, with the area under the receiver-operating characteristic curve (ROC) 0.83. High serum uric acid and C-reaction protein levels were risk factors for GDM independent of body mass indexes, with ORs 4.76 (95% CI: 2.08-10.90) and 3.10 (95% CI: 1.38-6.96), respectively. Predictive phenotype panel of GDM, together with the risk factors of GDM, will provide novel perspectives for the early clinical warning and diagnosis of GDM.
Research on Enterprise Digital Precision Marketing Strategy Based on Big Data
Authors: Kong Cheng
Published: August 2022

The combination and application of big data and machine learning in the offline consumer market makes the formulation of marketing strategies more scientific. The use of machine learning can make statistics and analysis of users’ consumption behavior and classify customers according to users’ consumption behavior, so as to realize the personalized promotion of marketing content. In this context, this paper carries out research on enterprise digital precision marketing strategy based on big data. Starting from the actual application, this paper analyzes the current problems faced by consumption data sharing, as well as the characteristic needs of precision marketing for consumer groups, introduces homomorphic encryption technology, completes the structural design, process design, and algorithm design of the scheme in combination with the actual scenario that enterprises need to carry out precision marketing for customers based on consumption data, describes each design link in detail, and verifies the feasibility of the algorithm in the scheme.
Design Method of Art Innovation Space Based on Computer Image Data Acquisition
Authors: Wu Lei , Xu Baoliang
Published: August 2022

With the development of science and technology, it brings more possibilities for artistic space design method innovation. The development of computer image data acquisition technology has realized the continuous extension of artistic space design and creation. Based on the computer image data collection technology, this paper realizes the innovative design of real and virtual environment in the exhibition of art space, centering on the interactive integration of the three elements of “human-objects-space.” Through the experimental design, from the space, color data collection, display space moving line, and space function design scheme were the four aspects of exploration and analysis. Compared with traditional design methods, the following conclusions are drawn: first, in spatial data acquisition, the average error of area measurement is less than 3.63%, and the measurement accuracy can reach more than 91%. Second, the average accuracy of color detection of various materials in space can be maintained at 90%. Third, the spatial movement line designed in this paper is simple and clear, with appropriate length, so that visitors can achieve the best visiting effect with the smallest distance. Fourth, the overall design scheme is reasonable, the space is transparent and bright, and the tour route is clear. It can complete the functional zoning design of the art exhibition space in a short time, saving a lot of manpower and time.
Encrypted Packet Inspection Based on Oblivious Transfer
Authors: Jia Xi , Zhang Meng
Published: August 2022

Deep packet inspection (DPI) is widely used in detecting abnormal traffic and suspicious activities in networks. With the growing popularity of secure hypertext transfer protocol (HyperText Transfer Protocol over Secure Socket Layer, HTTPS), inspecting the encrypted traffic is necessary. The traditional decryption-and-then-encryption method has the drawback of privacy leaking. Decrypting encrypted packets for inspection violates the confidentiality goal of HTTPS. Now, people are faced with a dilemma: choosing between the middlebox’s ability to perform detection functions and protecting the privacy of their communications. We propose OTEPI, a system that simultaneously provides both of those properties. The approach of OTEPI is to perform the deep packet inspection directly on the encrypted traffic. Unlike machine and deep learning methods that can only classify traffic, OTEPI is able to accurately identify which detection rule was matched by the encrypted packet. It can facilitate network managers to manage their networks at a finer granularity. OTEPI achieves the function through a new protocol and new encryption schemes. Compared with previous works, our approach achieves rule encryption with oblivious transfer (OT), which allows our work to achieve a better balance between communication traffic consumption and computational resource consumption. And our design of Oblivious Transfer and the use of Natural Language Processing tools make OTEPI outstanding in terms of computational consumption.
Rapid Progression of Heterotopic Ossification in Severe Variant of Fibrodysplasia Ossificans Progressiva with p.Arg258Gly in ACVR1: A Case Report and Review of Clinical Phenotypes
Authors: Hasegawa Kosei , Tanaka Hiroyuki , Futagawa Natsuko , Miyahara Hiroyuki , Tsukahara Hirokazu
Published: August 2022

Fibrodysplasia ossificans progressiva (FOP) is a rare skeletal disorder characterized by congenital malformation of the great toes and progressive heterotopic ossification. Malformation of the great toes appears at birth, while heterotopic ossification generally occurs during childhood and rarely occurs during infancy. Classical FOP results from the heterozygous p.Arg206His variant of the ACVR1 gene, which encodes Activin A receptor type 1. Recently, some atypical FOP patients with other ACVR1 gene variants and clinical features that are not observed in classical FOP patients have been reported. Herein, we describe a girl with severe FOP and multiple anomalies, including syndactyly of the hands and feet, nail agenesis, mandibular hypoplasia, heterotopic ossification occurring from infancy, and congenital cardiac malformation. In our patient, we identified de novo occurrence of the heterozygous p.Arg258Gly variant of ACVR1, which has previously been reported in only two severe FOP patients. Heterotopic ossification occurred earlier and more frequently compared with classical FOP patients. We present the time-series changes in heterotopic ossification in our patient and compare her clinical features with those of the previously reported patients with p.Arg258Gly. Our report deepens understanding of the clinical features in severe FOP with p.Arg258Gly and of FOP as a systemic disorder.
Fake Review Identification Methods Based on Multidimensional Feature Engineering
Authors: Wang Ge , Shang Guanglei , Pu Pengbo , Li Xuxin , Peng Hao
Published: August 2022

Product reviews in electronic platforms are very valuable to potential customers, product manufacturers, and product sellers. Their data contain huge business opportunities. Therefore, this paper analyzes the views, attitudes, and emotions expressed in these reviews. It presents three fake review identification methods based on multidimensional feature engineering. Under the premise of adding product feature extraction and opinion sentence judgment, six feature parameters are defined to identify fake reviews, and a fake review identification model based on multidimensional feature engineering is constructed. Then, the effectiveness of the selected feature engineering is verified. Based on the multidimensional feature engineering model, a fake review identification algorithm based on multidimensional feature engineering of union relationship, an identification algorithm based on weighted multidimensional feature engineering scoring, and an identification algorithm based on weighted multidimensional feature engineering classification are proposed. The execution effects of the three methods are compared. Fake review identification models based on multidimensional feature engineering can effectively filter fake reviews.
OCHSA: Designing Energy-Efficient Lifetime-Aware Leisure Degree Adaptive Routing Protocol with Optimal Cluster Head Selection for 5G Communication Network Disaster Management
Authors: Raja S. , Logeshwaran J. , Venkatasubramanian S. , Jayalakshmi M. , Rajeswari N. , Olaiya N. G. , Mammo Wubishet Degife
Published: August 2022

As an underlayment to cellular 5G communication network, device-to-device (D2D) communications will not only boost capacity utilization and power efficiency but also provide public health and public safety services. One of the most important requirements for these businesses is to have alternate access to cellular networks in the event that they are partially or completely disrupted as a result of a natural disaster. Despite limited communication coverage and bandwidth scarcity, the 3rd Generation Partnership Project (3GPP) must have developed a new device-to-device (D2D) communication method fundamental enhanced mobile that can strengthen spectral efficiencies besides allowing direct communication of gadgets in close propinquity devoid of transitory by elevated-node B (eNB). Unfortunately, enabling data transmission on a cellular connection offers a challenge in terms of two-way radio source administration, because D2D associates recycle cellular users’ uplink radio resources, which might create interference to D2D user equipment’s (DUE) receiving channels. In this study, we concentrate on optimal cluster head selection using the binary flower pollination optimization algorithm by designing an energy-efficient lifetime-aware leisure degree adaptive routing protocol named OptCH_L-LDAR. This topology is constructed with a multi-hop obliging communication system, instructed on the way to wrap an extensive remoteness connecting source and destination. The proposed OptCH_L-LDAR is compared with three state-of-art methods such as binary flower pollination (BFP) algorithm, time division multiple access (TDMA), and data-driven technique (DDT). As a result, the proposed OptCH_L-LDAR achieves 96% of energy efficiency, 89% of lifetime, 97% of outage probability, and 98% of spectral efficiency.
A Comprehensive Review on the Optimization of the Fused Deposition Modeling Process Parameter for Better Tensile Strength of PLA-Printed Parts
Authors: Mengesha Medibew Tesfaye
Published: August 2022

Fused Deposition Modeling (FDM) is a kind of Additive Manufacturing technology, which can produce complex parts by adding layer-by-layer mold automatically from 3D computer-aided design (CAD) data. Although the FDM process has its obvious merits, a fundamental backward factor of its professional enterprise acceptance is the inadequacy of higher mechanical properties and heavy structure of the manufactured product. For that reason, the properties of the manufactured product by FDM are highly dependent upon the choice of FDM parameters. Several studies are investigated to look at the effect of various FDM process parameters to improve print quality characteristics such as mechanical properties, build time, dimensional accuracy, and surface finish of the manufactured parts with having convenient process parameter settings. However, the progress has been gradual and not well organized because of the complex attributes of the FDM process and conflicting process parameters. This paper aims to comprehensively summarize recent studies of advanced statistical and experimental design techniques for better tensile strength of polylactic acid (PLA)-printed parts, the effect of process parameters on tensile strength, and the existing work on the optimization of process parameters.
Prognostic Significance of CCDC137 Expression and Its Association with Immune Infiltration in Hepatocellular Carcinoma
Authors: Bai Lu , Yang Zhao-Xu , Liu Jian-Shan , Wang De-Sheng , Yu Heng-Chao
Published: August 2022

Globally, hepatocellular carcinoma (HCC) is one of the most common causes of cancer-associated mortalities. The clinical outcome of HCC patients remains poor due to distant metastasis and recurrence. In recent years, growing evidences have confirmed that the coiled-coil domain-containing (CCDC) family proteins are involved in the progression of several diseases. However, the expression and clinical significance of the coiled-coil domain-containing 137 (CCDC137) in hepatocellular carcinoma (HCC) have not been investigated. Level 3 mRNA expression profiles and clinicopathological data were obtained in TCGA-LIHC. Differentially expressed genes (DEGs) were screened between 371 HCC and 50 nontumor specimens. The prognostic value of CCDC137 was analyzed in HCC patients. The correlations between CCDC137 and cancer immune infiltrates were investigated. In this study, a total of 2897 DEGs were obtained: 2451 genes were significantly upregulated and 446 genes were significantly downregulated. KEGG assays revealed that these DEGs were involved in tumor progression. Among 2897 DEGs, we found that CCDC137 expression was distinctly increased in HCC specimens compared with nontumor specimens. A high level of CCDC137 expression was related to an advanced tumor stage and grade. Moreover, patients with higher levels of CCDC137 expression had a shorter overall survival and disease-free survival than patients with lower CCDC137 levels. CCDC137 expression was positively correlated with infiltrating levels of several immune cells, such as CD8 T cells and Th2 cells. Finally, in vitro experiments confirmed that CCDC137 expression was highly expressed in HCC cells, and its knockdown suppressed the proliferation of HCC cells. Taken together, our findings revealed that CCDC137 might be used as a biomarker for immune infiltration and poor prognosis in HCC, which offered fresh insight on potential therapies for HCC.
Application of Internet Information Technology in College Music Education Teaching System
Authors: Zhu Ni
Published: August 2022

The development of society has higher and higher requirements on the quality of talents, and the demand for talents with comprehensive literacy continues to rise. Using music education as a means to continuously improve the music aesthetic quality of the new generation of young people and establish music aesthetic concepts is an important entry point to improve the quality of the whole people. But the current colleges and universities basically still focus on the traditional education and teaching methods, largely ignoring the importance of music education. In order to improve the comprehensive quality of college students, this paper introduces Internet information technology into the study of music system. The experimental results show that the research on the application of Internet information technology in the music system of colleges and universities can save time and management costs to a great extent and increase the efficiency of educational resources by 3.58%. At the same time, it can implement dynamic music evaluation, reasonably arrange students’ daily music training plans, improve students’ comprehensive quality and music literacy, and integrate music education into students’ lives, so as to increase the effect of music education to a great extent. Besides after the Internet information technology is applied to the music teaching system, the system can be linked with the network platform and resources, which greatly enriched teaching materials for music and information technology.
Electromyography Wearable Device Applied to the Medical Field
Authors: Hajjej Fahima , Alohali Manal Abdullah , Hasan Malek , Khan Md Maruf Haque
Published: August 2022

Electromyography is a diagnostic practice that examines the condition of the muscles and the nerves that regulate them. It allows neuromuscular disorders and lesions to be diagnosed, categorized based on their severity, and the most appropriate related treatment to be carried out based on the type of ailment detected. A neurologist or physical therapist is usually the one who performs this type of exam. The idea of carrying out this research arises from the need to work with a device that can perform the functions described so far to apply these medical studies to sports, physiotherapy, and rehabilitation to achieve full recovery after suffering a neuromuscular injury. This paper intends to work within the Internet of Medical Things (IoMT) to connect professionals and patients through the Internet and speed up diagnoses and treatments. This article discusses the design of a wearable electromyography device capable of performing the functions of acquisition, processing, and transmission of the signal generated by the muscles to diagnose and treat neuromuscular diseases or injuries. Specifically, the paper focuses on the design of a device that is capable of acquiring the signal generated by the muscles and processing the signal.
Successful Management in an Infant Patient of PHACE Syndrome with a Complicated Aortic Arch Anomaly
Authors: Suzuki Shun , Seki Mitsuru , Kataoka Koichi , Koga Reina , Sato Tomoyuki , Kawada Masaaki , Yamagata Takanori
Published: August 2022

PHACE syndrome is a congenital disorder often associated with a cervicofacial infantile hemangioma and complicated cardiovascular malformations. Patients with PHACE syndrome often have complex aortic arch anomalies, longer aortic stenosis or agenesis segments, and increased vascular tortuosity; therefore, perioperative management and surgical repair are challenging. We report a case of a female infant with PHACE syndrome and complex cardiovascular anomalies such as a double aortic arch associated with interruption of the left aortic arch, coarctation of the right aortic arch, patent ductus arteriosus, ventricular septal defect, and atrial septal defect. She was born at 36 weeks of gestation (birth weight, 2,150 g) and the diagnosis was confirmed by three-dimensional computed tomography. Because her patent ductus arteriosus did not close at first, her heart failure was managed preoperatively without prostaglandin E1. We initially attempted to promote weight gain. Surgical planning and simulation were performed using the patient-specific three-dimensional cardiovascular model created from computed tomography data. She underwent a successful aortic arch reconstruction by an end-to-side anastomosis with anterior patch augmentation at the age of 56 days. Detailed planning and simulation before surgery were vital in achieving favorable outcomes. Careful management and surgical planning using a patient-specific three-dimensional model are vital, especially in patients with complex malformations, such as in our case.
Urban Planning Design and Evaluation Based on GIS Information and Bayesian Network
Authors: Li Chunyan
Published: August 2022

In recent years, China’s urban construction has set off a climax, with the rapid increase of the number of cities and towns, the increasingly perfect functions of cities and towns, the continuous improvement of the level of urbanization, and the urban landscape changing with each passing day. Under the influence of many factors, urban planning and assessment are facing unprecedented pressure, leading to the inconsistency between the compilation results of planning. Under the guidance of system analysis and system dynamics, this paper designs and develops an urban planning information management system based on GIS (Geographic Information System) and Bayesian network, and then the system is applied to the field of urban planning. In this system, all kinds of data generated by planning are stored in order to realize the standardization of data, and then the urban planning work is guided by the effective management of the result data so as to know the implementation status of urban planning in time and provide the basis for the future planning and implementation.
Nanomaterial in Food Packaging: A Comprehensive Review
Authors: Barage Sagar , Lakkakula Jaya , Sharma Arushi , Roy Arpita , Alghamdi Saad , Almehmadi Mazen , Hossain Md. Jamal , Allahyani Mamdouh , Abdulaziz Osama
Published: August 2022

Food packaging industry is going through various scientific evolutions as per the preferences of the consumers along with the consumer trends. Current trends focus on not only protecting the food intelligently but also making it visually appealing to the consumer. In recent years, considerable attention is been given to replace nonbiodegradable materials with ecofriendly biodegradable composite material. Nanotechnology is flourishing and has proven to be a great incorporation to the packaging industry, as it can also overcome the drawbacks of the existing methods. Various nanomaterials have been explored and tested for manufacturing of packaging materials. In the present review, we discussed on current trends in food packaging and their drawbacks with respect to over consumption of plastic and how sustainable packaging is being implemented. Furthermore, nanotechnology is becoming a promising and widely used potential in food packaging industry along with nanomaterials currently being used such as zinc nanoparticles, polymer clay nanoparticles, and silver nanoparticles in food packaging. This information will broaden our current understanding on potential and problems associated with nanotechnology in food packaging.
Aggregation Technique Using Dynamic Cross-Propagation Clustering Algorithm in Wireless Body Sensor Networks
Authors: Arulprakash A. , Baalamurugan K. M. , Dhanaraj Rajesh Kumar , Sampath Kumar K. , Gupta Punit , Rehman Salma
Published: August 2022

Wireless body sensor networks (WBSNs) are characterized by a large number of battery-powered wireless sensor nodes, and the most challenging aspects of WBSNs are sensor node energy consumption, delay, and security (communication and data) while maintaining regular wireless sensor network (WSN) capabilities. Data aggregation, as a common procedure in data gathering applications, can waste a lot of energy since sensor nodes may stay in the listen to state even when they are not receiving data during the data collection process. In this research work, introducing the Self-Executing-Dynamic Cross-Propagation Clustering (SE-DCPC) algorithm helps to improve the node energy consumption positively by turning nodes to the accessible state when not in use and waking them up when necessary. The algorithm is energy-based and uses a self-executing-based dynamic cross-propagation clustering system to send/receive scheduling data in the WSN platform. The energy level of the nodes is the most essential component in constructing network communication, in contrast to earlier clustering algorithms. The purpose of this proposed algorithm is to enhance the traditional notion of the clustering algorithm (location-based clustering), leading to the primary goal of enhancing the permanence of the wireless sensor network, which is to conserve network coverage, using self-executing DCPC clustering technology for location and power. The result of performance analysis of the SE-DCPC is achieved by simulation using two different communication processes of clustering and intelligence decision-making methods. The numerical results shows that SE-DCPC can effectively handle and maintain a high rate of network node energy consumption. The simulation result shows that the proposed approaches securely obtain the high throughput and very minimal delay at the client side, compared to existing clustering algorithm approaches. This SE-DCPC algorithm increased by 21.89% the communication medium lifetime and by 37% the energy consumption and reduced by 23.27% the overhead compared with existing clustering algorithms.
Precise Positioning of Redundant Robot Motion Energy-Saving Control Based on Sensing Technology
Authors: Lu Yaping
Published: August 2022

In order to provide intelligent drinking water service for human beings, an intelligent indoor positioning water delivery system is proposed. The system can realize the functions of automatic filling water and so on. Based on the UP Squared processor, the system extends the UWB positioning Zigbee wireless transmission gyroscope manipulator and other functional modules. Based on the UP Squared processor, the system extends the UWB positioning Zigbee wireless transmission gyroscope manipulator and other functional modules. MPU6050 module was used to sense the rotation angle, and PID algorithm was used to control the rotation of redundant robot. The position of water cup is sensed based on current magnetic effect and electromagnetic induction law. Ultrasonic module is used to detect the rising height of the outlet and the water level in the cup. Several parameters of the system, such as orientation, distance adjustment, and power consumption, and the whole process of water delivery are tested through experiments. The experimental results show that the designed robot has a measurement accuracy of 1 cm, a total of static power of 5.35 W, and a total of dynamic power of 13.6 W. Conclusion. The system has the characteristics of accurate positioning, fast and smooth steering, and low power consumption, which can meet the technical requirements of practical application in indoor intelligent positioning water delivery.
Experimental and Numerical Studies on Bond Quality of Fully Grouted Rockbolt under Confining Pressure and Pull-Out Load
Authors: Yu Shuisheng , Niu Leilei , Chen Jin
Published: August 2022

In mining engineering, the in situ stress changes with the stress induced by the surrounding mining activities. It positively or negatively affects the propagation of ultrasonic guided waves in rockbolts. Therefore, the effect of in situ stress in rockbolt support was determined by applying confining pressure and pull-out load in a laboratory test and using ultrasonic guided waves to test the rockbolt. Furthermore, the propagation law of ultrasonic guided waves and bond quality of the rockbolt under the interaction of the pull-out load and confining pressure were studied. Numerical simulations were performed to deduce the guided wave propagation process in grouted systems, and the influencing mechanism of the pull-out load and confining pressure on the guided wave propagation was discussed. The laboratory test and numerical simulation results show that the confining pressure weakens the guided wave propagation without pull-out load. Under the same pull-out load, the guided wave propagation gradually strengthens with increasing confining pressure. A larger confining pressure weakens the weakening effect of the pull-out load and suppresses the discreteness of the guided wave propagation. Under the same confining pressure, the guided waves did not diffract well into the cement mortar and concrete with increasing pull-out load, the confining pressure restricted the radial vibration of the guided waves, and the guided wave propagation law weakened. Thus, the pull-out load plays a weakening role in the propagation law of ultrasonic guided waves.
Impact Assessment of Interlocking Systems on Single-Track Railway Lines as a Measure Leading to Resilient Railway System
Authors: Bažant Michael , Bulíček Josef
Published: August 2022

Railway systems should be resilient to play a key role in creating sustainable development. Single-track railway lines are seen as potential bottlenecks due to limited capacity. More advanced railway interlocking systems (such as ETCS or satellite-based control systems) are being developed. On the other hand, the installation of these interlocking systems is a complex and time-consuming and costly task. For this reason, it is necessary to recognize the impact of potentially installed system with capacity, stability of timetable, quality, and other associated effects. The assessment is based on a set of simulation experiments using stochastic microscopic simulation model in the OpenTrack software tool. The focus is on railway operation with automatic block and automatic line blocking systems. If these two systems will have positive capacity effects, it is a basic presumption also for systems such as moving block (e.g., ETCS L3) to be effective. Research has shown that the significance of such measures can be best supported by linking to a matching timetable concept that will make full use of the benefits offered by these interlocking systems. The results reached in this research should be potentially applied, for example, by prioritizing of single-track railway lines for possible installation of such interlocking system. It can be achieved based on the capacity and operational effects examined.
Investigation on Mechanical Durability Properties of High‐Performance Concrete with Nanosilica and Copper Slag
Authors: Kumar Raj , Natarajan Suganya , Singh Rahul , Rajput Vinod Singh , Loganathan Ganesh Babu , Kumar Sanjeev , Sakthi T. , Mahseena Akter Meem
Published: August 2022

Mineral admixtures are frequently utilized as cement substitution materials in high‐performance concrete (HPC), and so many studies have explored the influence of mineral admixtures on the rheological behavior of HPC. Investigations were done to examine the impact of nanosilica less than 100 nm on HPC by substituting copper slag at a fixed substitution of forty percent for fine aggregate. Concrete samples were cast by substituting cement with nanosilica at (0.5, 1, 1.5, 2, 2.5, and 3) percentages. Examinations on mechanical properties and durability were done on specimens. The above tests demonstrated an increase in water demand because of the increase in the nanosilica substitution percentage. Mechanical and durability properties were improved at a larger rate with the incorporation of nanosilica. The outcomes indicated that colloidal nanosilica is an effective material that enhances the microstructure and acts as a catalyst for pozzolanic activity. The incorporation of nanosilica improves the strength up to two percentage substitution level.
Application of Linear Additive Conditions for Near-Infrared Diffuse Reflectance Absorption Spectroscopy
Authors: Feng Zhiyue , Cai Guimin , Huang Tiancheng , Liu Hubin , Zheng Jianhua , Yang Zengrong , Zhao Longlian , Li Junhui
Published: August 2022

Determining the homogeneity of material mixing in real time during product processing is critical for quality control. According to the Kubelka–Munk (K-M) function of diffuse reflectance absorption spectrum, absorbance (A) is approximately linear with the content of the components when the sample scattering coefficient (S) is in a certain range. The S is determined by the particle size of powder samples. Therefore, this study determined particle size ranges that satisfy linear additivity in near-infrared diffuse reflectance spectroscopy (NIRDRS). Thus, the proposed NIRDRS analysis technique can be used to determine the homogeneity of material mixes or analyze the percentages of the components in the mixture. In this study, vitamin B3 and vitamin C were used for preparing mixed samples with varying percentages. The experimental results revealed that linear additivity is satisfied when the powder particle size is in the range of less than 280, 280–450, and 450–900 μm. When the confidence level is 0.01, the actual mixed spectra are not significantly different from the “simulated mixed spectra” constructed by linear addition, with their relative deviations less than 1.08%. The absolute errors of the actual and analytic percentages were within 2.98% for each component in the mixtures. The above conclusions also hold for sorghum, which has a complex material composition. Statistical models cannot analyze the percentages of components in the mixture. In contrast, linear addition and direct calibration approach avoids the use of a large number of samples for statistical modeling and analyze the percentages of mixed samples. Meanwhile, it can be used to discriminate and analyze the material mixing uniformity by building a mechanistic model.
Diagnose Diabetic Mellitus Illness Based on IoT Smart Architecture
Authors: Pati Abhilash , Parhi Manoranjan , Pattanayak Binod Kumar , Singh Debabrata , Samanta Debabrata , Banerjee Amit , Biring Sajal , Dalapati Goutam Kumar
Published: August 2022

Obtaining a quick remote diagnosis of heart disease has proven problematic in recent days. To overcome such issues in e-Healthcare systems, Internet of Things (IoT) applications have been deployed using cloud computing (CC) approaches. There are still a number of disadvantages to using CC, including latency, bandwidth, energy usage, and security and privacy concerns. Fog computing (FC), a CC development, may be able to overcome these obstacles. DiaFog enabling remote users for real-time diagnosis of diabetic mellitus disease (DMD) has been proposed in this study, which is based on the combined ideas of IoT, cloud, and fog computing, as well as an ensemble deep learning (EDL) technique. The proposed system is trained with EDL approaches on the integrated dataset of two diabetes mellitus disease datasets (DMDDs), namely, Pima Indians Diabetes Dataset (PIDD) and Hospital Frankfurt Germany Diabetes Dataset (HFGDD), obtained from the UCI-ML and Kaggle repository, respectively, and the integrated dataset of these two. The suggested system has been used to demonstrate accuracy, precision, recall,

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-measure, latency, arbitration time, jitter, processing time, throughput, energy consumption, bandwidth utilization, network utilization, scalability, and more. In the remote instantaneous diagnosis of diabetic patients, the integration of IoT-fog-cloud is useful. The results of the trials show the value of employing FC principles and their applicability for speedy diabetic patient remote diagnosis. PACS-key is describing text of that key PACS-key describing text of that key.
Permanent Magnet Flux Linkage Identification Method of the Model Predictive Current Control System for PMSM
Authors: Chen Tao , Xiao Haihong
Published: August 2022

Accurate identification of permanent magnet flux linkage can effectively improve the control performance of model predictive current control system of permanent magnet synchronous motor (PMSM). This paper reviews the existing identification methods of permanent magnet flux linkage of PMSM first and then proposes an identification method of permanent magnet flux linkage based on an improved unscented particle filter, the problem of particle diversity reduction of the traditional unscented particle filtering algorithm is solved, and the identification performance of permanent magnet flux is improved. Simulation research and experimental verification of the proposed method are carried out, and the simulation and experimental results confirm the effectiveness of the proposed method.
Evaluation and Analysis Model of Economic Development Level for Latin American Countries
Authors: Cui Hao
Published: August 2022

This study is devoted to the analysis of high-quality economic development in Latin American countries. Under the guidance of the new development concept strategy, the evaluation index system for the high-quality economic development level of Latin American countries is constructed from the six dimensions of economic strength, innovation, coordination, green, openness, and sharing, and the entropy weight method is used to calculate the weight of each evaluation index. Based on UTM projection coordinate quantification and K-Means clustering algorithm, the spatial effect clustering model of Latin American countries is established. According to the two dimensions of geographical location and comprehensive index, Latin American countries are divided into different economic zones, and the agglomeration effect in the process of economic development of Latin American countries is analyzed from a spatial perspective.
A Game-Theoretic Scheme for Parked Vehicle-Assisted MEC Computation Offloading
Authors: Chen Ruoyu , Fan Yanfang , Jia Mengxin , Yuan Shuang
Published: August 2022

By offloading computation tasks, multi-access edge computing (MEC) supports diverse services and reduces delay and energy consumption of mobile devices (MDs). However, limited resources of edge servers may be the bottleneck for task computing in high-density scenarios. To address this challenge, by leveraging the underutilized resources of parked vehicles to execute tasks, we propose a parked vehicle-assisted multi-access edge computing (PV-assisted MEC) architecture, which enables MEC servers to expand their capability flexibly. To achieve efficient offloading, we propose a PV-assisted MEC offloading scheme in a multi-MD environment. We design a game-based distributed algorithm to minimize the overhead of MDs and further reduce the burden on the MEC server. Simulation results show that compared with the common MEC system, our scheme can reduce the burden on the MEC server by 5% and the offloading overhead by 17%.