bluuebunny/crossref_metadata_2025 huggingface dataset:
AI Recognition Method of Pronunciation Errors in Oral English Speech with the Help of Big Data for Personalized Learning
Authors: Liu Yanqing , Quan Qiaoli
Published: May 2022

At present, there is a lack of careful consideration in the judgment process of pronunciation errors in many English speeches. These pronunciation errors will create a great impact on personalized learning. The process of creating a data set for errors is also not an easy work. On considering the above obstacle, an artificial intelligent recognition method of pronunciation errors in English speeches for personalized learning along with big data is proposed. This method takes the average pronunciation level of standard speech as the basis of pronunciation error judgment, and judges the pronunciation and application of words such as speed, pronunciation, semantics, etc. In the Hidden Markov Model (HMM) modelling method of speech recognition, Viterbi algorithm and improved posterior probability algorithm are implemented to recognize student’s vocalization instinctively. Through the segmentation and scoring of basic units, English learners are provided with reliable pronunciation information feedback, correct pronunciation errors and give corresponding feedback according to the judgment results. The innovation outcome establishes that the intelligent recognition method for personalized learning can efficiently diminish the error rate and enhance the accuracy of error detection. Let the artificial intelligence (AI) correct English learner’s pronunciation errors intelligently.
Applications of Machine Learning in Knowledge Management System: A Comprehensive Review
Authors: Simon Casper Gihes Kaun , Jhanjhi Noor Zaman , Goh Wei Wei , Sukumaran Sanath
Published: May 2022

As new generations of technology appear, legacy knowledge management solutions and applications become increasingly out of date, necessitating a paradigm shift. Machine learning presents an opportunity by foregoing rule-based knowledge intensive systems inundating the marketplace. An extensive review was made on the literature pertaining to machine learning which common machine learning algorithms were identified. This study has analysed more than 200 papers extracted from Scopus and IEEE databases. Searches ranged with the bulk of the articles from 2018 to 2021, while some articles ranged from 1959 to 2017. The research gap focusses on implementing machine learning algorithm to knowledge management systems, specifically knowledge management attributes. By investigating and reviewing each algorithm extensively, the usability of each algorithm is identified, with its advantages and disadvantages. From there onwards, these algorithms were mapped for what area of knowledge management it may be beneficial. Based on the findings, it is evidently seen how these algorithms are applicable in knowledge management and how it can enhance knowledge management system further. Based on the findings, the paper aims to bridge the gap between the literature in knowledge management and machine learning. A knowledge management–machine learning framework is conceived based on the review done on each algorithm earlier and to bridge the gap between the two literatures. The framework highlights how machine learning algorithm can play a part in different areas of knowledge management. From the framework, it provides practitioners how and where to implement machine learning in knowledge management.
E-Banking Continuance: An Integration of Network Externalities and Flow Theory
Authors: Onyina Ernestina , Owusu Kwateng Kwame , Dzidzah Esther
Published: May 2022

This study examines the effect of network externalities and flow on continual usage of e-banking services. A sample of 400 e-banking users was conveniently engaged using a structured questionnaire. The method of analysis used included Spearman’s correlation analysis, confirmatory factor analysis and structural equation modelling analysis. The findings indicate that referent network size does not significantly influence continuance intention of e-banking users. However, flow positively influences continuance intention of e-banking users. Stakeholders in the financial institutions will understand the driving factors behind continual usage of e-banking services. Some researchers have explored continual usage of e-banking but such studies are rare in the African context. This study will contribute to extant literature by adding a new dimension, intrinsic and extrinsic factors, of e-banking continual usage.
MWCNTs and MoS2-Sensitized BiVO4 Photoanode for Improved Hydrogen Peroxide and Hypochlorite Sensing
Authors: Lu Longxi , Cai Ran , Li Ye , Lu Ye , Hu Guoqing , Lin Junming
Published: May 2022

Multi-walled carbon nanotube (MWCNT)-modified MoS2/BiVO4 was manufactured and used for the photoelectrochemical (PEC) detection of hydrogen peroxide (H2O2) and hypochlorite (ClO−). A solvothermal method was used to synthesize an MWCNT/MoS2/BiVO4 composite that showed perfect PEC properties because the MWCNTs and MoS2/BiVO4 heterostructures increased the composite’s stability against photocorrosion. Compared with the same signal of MWCNT/MoS2/BiVO4, the photocurrent signal of other composites was much smaller upon irradiation by visible light. According to this PEC sensor, the linear range of the H2O2 concentration was 1–200[Formula: see text][Formula: see text]M and 280–1560[Formula: see text][Formula: see text]M at [Formula: see text] based on the same pH when detecting ClO− concentrations between 0.5–10[Formula: see text][Formula: see text]M and 20–340[Formula: see text][Formula: see text]M in a bleach sample. As a result, this sensor can be used to detect reactive oxygen species (ROS) in practical samples.
International Debts Flows
Authors: Hung Ly Dai , Anh Bui Thi Hai , Thanh Vo Tri
Published: May 2022

This paper analyzes the dependence pattern of net debts inflows on the sovereign debts rating and the fiscal balance, on accounting for the productivity growth rate. The cross-section evidence on a sample of 149 economies for the period from 1990 to 2019 uncovers that a higher sovereign debts rating, a lower fiscal balance or a higher productivity growth is associated with more net debts inflows. Thus, the debts flows are underlined by the store of wealth accumulation across economies. Moreover, there exists a nonlinearity on the pattern of debts flows, for which the fiscal balance determines the impact of sovereign debts rating on the net debts inflows. The results are robust for panel data regression as well as case study of three economies including Japan, Thailand and Vietnam.
Crucial Events and Biology
Authors: Grigolini Paolo
Published: May 2022

In the last years of the 20th century, the attention of physicists working in statistical physics moved from equilibrium processes characterized by stationary correlation functions and Poisson dynamics to biological processes exhibiting ergodicity breaking. The discovery of these processes raised a debate on whether basic properties such as the Onsager principle had to be abandoned or properly revisited. 1 The discovery of Levy processes led many researchers to replace the conventional central limit theorem with the generalized central limit theorem, responsible for a striking departure from the ordinary Gaussian statistics. The discovery of the processes of self-organization made the study of avalanches become very popular. 2 The observation of turbulent processes led to the discovery of new waiting time distribution densities, characterized by inverse power laws 3 and a new stochastic central limit theorem was invented to explain the emergence of Mittag-Leffler function, which is now widely used for the foundation of fractional derivatives. 4 The traditional Linear Response Theory of Kubo was replaced by a new form of linear response, compatible with the ergodic breakdown of complex systems, and this new form of linear response was used for the foundation of Complexity Matching (CM). 5 I plan to prove that crucial events are responsible for ergodicity breaking and that the CM phenomenon is a manifestation of crucial events. One problem still open in this field of research is the origin of [Formula: see text] noise that is traditionally interpreted as a manifestation of the Mandelbrot Fractional Brownian Motion (FBM). 6 I plan to show that the [Formula: see text] noise proposed in 5 for the foundation of the CM phenomenon has a completely different nature, involving crucial events rather than the FBM infinite memory. A recent result of my research group 7 proved that the progress of autonomic neuropathy makes the heartbeats of healthy individuals, dominated by crucial events, turn into FBM. Quite surprisingly, the same phenomenon of transition from the crucial event to the FBM regime was observed in the germination process of lentils 8 in the absence of light. The transition from Levy to Gauss statistics is supposed to be generated by environmental fluctuations and I will illustrate the experimental and theoretical research works that will shed light into their nature.
Characterization and Identification of Fungal Conidia via Shifted Excitation Raman Difference Spectroscopy
Authors: Han Zehua , Strycker Benjamin D. , Commer Blake , Wang Kai , Shaw Brain D. , Scully Marlan O. , Sokolov Alexei V.
Published: May 2022

Fungi can be found everywhere, and their impacts on human beings are numerous and varied. Fungi have been widely used in the food, biofuel, beverage and pharmaceutical industries. 1 However, uncontrolled fungal growth can be costly to agriculture, forestry and livestock. If they feed on humans, diseases can be induced such as ringworm, athlete’s foot and lung infections. Some effects on human health may last over years and even lifetimes. 2 It requires timely and accurate identification of mold species to evaluate and/or prevent damage from mold growth, and minimize the consequences of mold exposure. Raman spectroscopy studies on mold spores have been proposed and implemented as a method to identify fungal species. However, the presence of fluorescence emission always hinders Raman signal detection and is virtually impossible to avoid, especially in biological specimens. Shifted excitation Raman difference spectroscopy (SERDS) is a very powerful technique to separate Raman contribution from fluorescence contribution. Herein, we adopt the SERDS modality to extract pure Raman signals from fungal conidia of different species and find that Raman signatures of spores generated from pigment molecules bounded within the cell walls. 3 A further study of conidia of different mold species indicates that the major features of the Raman spectrum correlate with the melanin biosynthesis pathway: species that produce the same melanin exhibit similar Raman spectra. 4 , 5
Exploration of New Sensitizers for Photodynamic Therapy Targeting Deep Cancer Treatment
Authors: Chen Wei
Published: May 2022

Despite its advantages, photodynamic therapy (PDT) has one major drawback: penetration depth. This limits the use of conventional PDT methods to skin (surface) tumors only, making it ineffective for deep tumors. There are four possible solutions for the light delivery for deep tumor treatment: particles activated by near-infrared (NIR) light, up-conversion of nanoparticles that absorb NIR light and emit visible light for other photosensitizers (PSs), fiber optics and ionizing X-rays. Of these options, the best is X-rays. Near-infrared light can penetrate only 5[Formula: see text]mm in tissue while retaining enough energy to activate the PSs. The use of fiber optics is neither convenient nor efficient as it cannot effectively and evenly activate the photosensitizers. It is also almost impossible for the treatment of metastatic sites or lymph nodes involved with this disease, unless they are located in the region where light delivery is feasible. In contrast with the other methods, X-rays can easily penetrate as deeply as necessary into the patients, and are convenient as they are commonly used in cancer therapy.

The use of novel copper–cysteamine (Cu–Cy) nanoparticles is a good solution for overcoming these issues because Cu–Cy nanoparticles can be effectively activated by X-rays to produce singlet oxygen, which makes it very efficient for deep cancer treatment. Here, I will discuss the use of copper–cysteamine nanoparticles to enhance radiation therapy in combination with PDT and targeting therapies.
Laser Spectroscopic Tools for Nano-Biophotonics
Authors: Sokolov A. V.
Published: May 2022

Biophotonics is a vibrant interdisciplinary field exploring the interaction between electromagnetic radiation and biological materials such as sub-cellular structures and molecules in living organisms. Biophotonics research leads to applications in agriculture and life sciences and produces tools for medical diagnostics and therapies. Working in this general field, we have recently made advances toward ultrasensitive Raman-spectroscopic probing of viruses. Our approach is based on laser spectroscopy aided by plasmonic nanoantennas, as in tip-enhanced Raman spectroscopy (TERS). An additional enhancement in sensitivity and speed is obtained by employing the femtosecond adaptive spectroscopic technique (FAST) for coherent anti-Stokes Raman scattering (CARS). The combined approach shows promise for non-destructive label-free bioimaging with molecular-level sensitivity and with spatial resolution down to a fraction of a nanometer.
LiDetector
: License Incompatibility Detection for Open Source Software
Authors: Xu Sihan , Gao Ya , Fan Lingling , Liu Zheli , Liu Yang , Ji Hua
Published: May 2022

Open-source software (OSS) licenses dictate the conditions, which should be followed to reuse, distribute, and modify software. Apart from widely-used licenses such as the MIT License, developers are also allowed to customize their own licenses (called custom license), whose descriptions are more flexible. The presence of such various licenses imposes challenges to understand licenses and their compatibility. To avoid financial and legal risks, it is essential to ensure license compatibility when integrating third-party packages or reusing code accompanied with licenses. In this work, we propose
LiDetector
, an effective tool that extracts and interprets OSS licenses (including both official licenses and custom licenses), and detects license incompatibility among these licenses. Specifically,
LiDetector
introduces a learning-based method to automatically identify meaningful license terms from an arbitrary license, and employs Probabilistic Context-Free Grammar (PCFG) to infer rights and obligations for incompatibility detection. Experiments demonstrate that
LiDetector
outperforms existing methods with 93.28% precision for term identification, and 91.09% accuracy for right and obligation inference, and can effectively detect incompatibility with 10.06% FP rate and 2.56% FN rate. Furthermore, with
LiDetector
, our large-scale empirical study on 1,846 projects reveals that 72.91% of the projects are suffering from license incompatibility, including popular ones such as the MIT License and the Apache License. We highlighted lessons learned from perspectives of different stakeholders and made all related data and the replication package publicly available to facilitate follow-up research.
Constitutions vs. COVID-19: CrowdLaw as an Alternative in Crisis and Recovery
Authors: Sierra Jose M. Martinez
Published: May 2022

Coronavirus has activated the main constitutional mechanisms set in place to face exceptional circumstances in all countries that can be considered consolidated democracies. Constitutional systems make it possible for constituent powers to limit fundamental rights that are the cornerstone for the full exercise of citizenship in a democracy. Thus, for example, lockdowns and limitations on gatherings,
de iure and de facto
, limit or eliminate the right to assembly.

Exception—constitutional instruments, that also allow for the transfer of parliamentary functions to the Executive power, are mostly designed, and many times thought to be exclusively used in extreme circumstances: wars or natural disasters that have an immediate impact on millions of people (causing death, the loss of the home or massive displacement, etc.). In these cases, it is assumed that parliaments and citizens must enter survival mode, and because of that, there is no reason to think that any type of citizen participation is possible.

However, despite the gravity of COVID-19, the situation does not conform to the pattern I have just described. Most citizens, surely those that tend to participate in the ordinary democratic process, have been able to adapt their lives to the confines of their own homes thanks to civic responsibility and technology: work, education, socialization, shopping, etc. If this is so, why has the decision-making process not been able to adapt to the COVID pandemic? Furthermore, if citizen input is essential to control the situation and social distancing is a must, why is technology not the cornerstone of citizen's data recollection?

This work analyzes the existing constitutional framework and the main governmental measures (norms and actions) adopted, in order to detect in which stages (out of the five basic policy and law-making stages) citizen participation could have been integrated, and how CrowdLaw might have helped to make participation more effective, and if CrowdLaw can help palliate the constitutional impact resulting from a pandemic, particularly in regard to the exercise of citizen participation, and in improving the quality and effectiveness of any measure that has been adopted. I argue that constitutional norms are compatible with CrowdLaw because they do not rule out the activation of CrowdLaw procedures neither in normal nor in exceptional circumstances.
Understanding the Impacts of Bacteriophage Viruses: From Laboratory Evolution to Natural Ecosystems
Authors: Koskella Britt , Hernandez Catherine A. , Wheatley Rachel M.
Published: May 2022

Viruses of bacteria (bacteriophages or phage) have broad effects on bacterial ecology and evolution in nature that mediate microbial interactions, shape bacterial diversity, and influence nutrient cycling and ecosystem function. The unrelenting impact of phages within the microbial realm is the result, in large part, of their ability to rapidly evolve in response to bacterial host dynamics. The knowledge gained from laboratory systems, typically using pairwise interactions between single-host and single-phage systems, has made clear that phages coevolve with their bacterial hosts rapidly, somewhat predictably, and primarily by counteradapting to host resistance. Recent advancement in metagenomics approaches, as well as a shifting focus toward natural microbial communities and host-associated microbiomes, is beginning to uncover the full picture of phage evolution and ecology within more complex settings. As these data reach their full potential, it will be critical to ask when and how insights gained from studies of phage evolution in vitro can be meaningfully applied to understanding bacteria-phage interactions in nature. In this review, we explore the myriad ways that phagesshape and are themselves shaped by bacterial host populations and communities, with a particular focus on observed and predicted differences between the laboratory and complex microbial communities.
Science and Technology of Complex Correlated Oxides: The Legacy of John Goodenough
Authors: Ramesh R.
Published: May 2022

Summary. Its an absolute pleasure to be able to write this article to honor Professor John Goodenough on his 100th birthday. John, here is wishing you many more years of wonderful science with mirth and laughter! I have had the pleasure of knowing John for more than two decades and also following in his footsteps (albeit at a great distance from him), working on complex correlated oxides for my entire professional career, starting from the Hi-TC cuprates, manganites that display colossal magnetoresistance, ferroelectricity and most recently looking at the coupling between electricity and magnetism in multiferroics as well as the intricacies of spin transport in correlated oxides. This article is written on behalf of many colleagues, collaborators, and researchers in the field of complex oxides as well as current and former students and postdocs who continue to enable and undertake cutting-edge research in the field of multiferroics, magnetoelectrics, and broadly correlated electron materials physics as well as the pursuit of electric-field control of magnetism. What I present is something that is extremely exciting from both a fundamental science and applications perspective and has the potential to revolutionize the field of microelectronics. To realize this potential will require numerous new innovations, both in the fundamental science arena as well as translating these scientific discoveries into real applications. Thus, this article attempts to bridge the gap between fundamental materials physics and the actual manifestations of the physical concepts into real-life applications, a spirit that John’s entire career has embraced.
Topology Optimization of 3D Flow Fields for Flow Batteries
Authors: Lin Tiras Y. , Baker Sarah E. , Duoss Eric B. , Beck Victor A.
Published: May 2022

As power generated from renewables becomes more readily available, the need for power-efficient energy storage devices, such as redox flow batteries, becomes critical for successful integration of renewables into the electrical grid. An important aspect of a redox flow battery is the planar flow field, which is usually composed of two-dimensional channels etched into a backing plate. As reactant-laden electrolyte flows into the flow battery, the channels in the flow field distribute the fluid throughout the reactive porous electrode. We utilize topology optimization to design flow fields with full three-dimensional geometry variation, i.e., 3D flow fields. Specifically, we focus on vanadium redox flow batteries and use the optimization algorithm to generate 3D flow fields evolved from standard interdigitated flow fields by minimizing the electrical and flow pressure power losses. To understand how these 3D designs improve performance, we analyze the polarization of the reactant concentration and exchange current within the electrode to highlight how the designed flow fields mitigate the presence of electrode dead zones. While interdigitated flow fields can be heuristically engineered to yield high performance by tuning channel and land dimensions, such a process can be laborious; this work provides a framework for automating that design process.
Sanitary Ware Waste as a Source for a Valuable Biodiesel Catalyst
Authors: Roushdy Mai Hassan
Published: May 2022

Biofuel is a type of fuel that is made from biomass using modern techniques rather than the relatively slow geological processes that lead to the development of fossil fuels. In Europe, biodiesel is the most widely used biofuel. The sanitary ware industry generates a lot of hazardous waste, such as waste gypsum molds. These molds are broken, pulverized, and reacted with NaCO3 to make CaCO3, which is then heated to produce CaO. The resulting CaO catalyzes the reaction between waste frying oil and methanol for biodiesel synthesis. To evaluate the effect of reaction parameters on the production of biodiesel, the independent reaction parameters that were chosen are as follows: reaction temperature in the range 50–70°C, methanol to oil (M:O) molar ratio in the range 9–15, catalyst loading in the range 1–5%, and time in the range 2–6 hrs. The influence of the independent factors on the reaction-dependent responses was evaluated and it was found that reaction temperature and methanol-to-oil ratio have a major effect on the biodiesel yield. Reaction condition optimization has been studied to maximize biodiesel yield at minimum reaction conditions. The optimum process conditions are 93.4% biodiesel yield at an M:O molar ratio of 15 : 1, catalyst loading of 1%, reaction temperature of 53.6°C, and reaction time of 2 h. The results showed that resulted biodiesel catalyst (CaO) can be used one time; then, a fresh catalyst will be used.
Medical Data Analysis of Lumbar Disc Herniation Patients after Traditional Chinese Medicine Rehabilitation Intervention Lumbar Function Recovery
Authors: Yan Liu , Chenni Wang , Fang Liu , LiyueYang
Published: May 2022

In order to study the efficacy of TCM rehabilitation for lumbar disc herniation, it is suggested to compare the effects of hot compress, ordinary sandbag, or hot compress with traditional Chinese medicine. A total of 79 patients with Qi stagnation and blood stasis syndrome in a traditional Chinese medicine hospital who met the diagnostic criteria of LDH and the syndrome classification in the diagnostic efficacy criteria of traditional Chinese medicine were selected. The subjects were randomly divided into groups A, B, and C: group A (26 cases) was the sandbag hot compress dry pregroup and received the simple sandbag hot compress scheme; group B (26 cases) was a simple traditional Chinese medicine hot compress intervention group, which received traditional Chinese medicine hot compress scheme; group C (27 cases) was the intervention group of traditional Chinese medicine sandbag combined with hot compress and received the scheme of traditional Chinese medicine sandbag combined with hot compress. In addition to the different hot compress media used, other aspects remained the same among the three groups. The treatment time of each hot compress was 40 min, twice a day for 2 weeks. A total of 14 cases fell out during the intervention process, and 65 subjects completed the intervention process. The experiment showed that there was no significant difference among the three groups (P>0.05). The test results were confirmed.
Machine Learning Model-Based Applications for Food Management in Alzheimer’s Using Regression Analysis Approach
Authors: Kumhar Sajadul Hassan , Kapula Prabhakara Rao , Kaur Harveen , Krishna Radeep R. , Kirmani Mudasir M , Athavale Vijay Anant , Ahmad Mohd Wazih
Published: May 2022

Alzheimer’s disease (AD) has become a public health concern due to its misinterpretation with vascular dementia (VD) and mixed dementia Alzheimer’s disease (MXD). Therefore, an accurate differentiation of these diseases is essential for improving the treatment procedure. It has been seen that nutrition along with several other factors plays a role in the disease progression. Scientists are trying to find a solution using some machine learning (ML) techniques. The ML algorithms used for this purpose are neural networks, support vector machines, regression and many more. The current research is focused on understanding the extent of the application of machine learning tools in enhancing food management for patients with Alzheimer’s since there is no cure known for the same. A total of 100 patient data have been collected where the patients had AD, VD, and MXD. Their demographic data, dietary intake, Fazekas scores, and Hachinski scores were collected (independent variables) and analysed in IBM SPSS by considering the risk of development of AD, VD, and MXD as dependent variables. The findings showed that age is highly related (

p
<
0.001

) to the development of these three diseases and other demographics are not prioritized. Discussion of other available journal articles showed that nutritional intake, Fazekas scores, Hachinski scores, and gender are also indicators for predicting these diseases (

p
<
0.001

). Thus, this study concluded that age, gender, diet consumption, and Fazekas and Hachinski scores are important indicators for differentiating AD from other diseases, and ML can be used to create a custom nutrition plan based on the patient’s diet and stage of disease progression. Lastly, future scopes of ML have been explained in this paper.
Evaluation of Nursing Effects of Pelvic Floor Muscle Rehabilitation Exercise on Gastrointestinal Tract Rectal Cancer Patients Receiving Anus‐preserving Operation by Intelligent Algorithm‐based Magnetic Resonance Imaging
Authors: Zhang Lijuan , Wang Feng
Published: May 2022

Based on magnetic resonance imaging (MRI) technology under artificial intelligence algorithm, the postoperative nursing effects of pelvic floor muscle rehabilitation exercise on gastrointestinal tract rectal cancer (RC) patients were investigated. A total of 88 patients receiving RC anus‐preserving surgery in hospital were selected. The included patients were divided randomly into the experimental group (44 cases) and the control group (44 cases). Patients in the control group engaged in Kegel motion, while patients in the experimental group underwent self‐designed comprehensive pelvic floor training. Anorectum function rating scale and quality of life questionnaire for colorectal cancer (EORTC QLQ‐CR29) were utilized to compare and analyze anus functions and living quality of patients in the two groups. Besides, all patients in two groups received MRI examinations, and images were processed by a convolutional neural network (CNN) algorithm. The results showed that in MRI images, there were significant signal differences between lesion tissues and normal tissues. After being processed by an artificial intelligence algorithm, the definition of MRI images was remarkably enhanced with clearer lesion edges. The quality of images was also significantly improved. Besides, the comparison of anus functions of patients in two groups showed that the differences demonstrated statistical meaning after the intervention (P < 0.05). In conclusion, artificial intelligence algorithm‐based MRI and comprehensive pelvic floor muscle exercise showed significant application prospects and values in the recovery of patients’ intestinal functions after RC anus‐preserving surgery.
Intelligent Campus and English Visual Education System Design Based on Internet of Things
Authors: Li Qi
Published: May 2022

With the continuous development of the Internet of Things technology, learning and acquiring knowledge through Internet will become an important way for human beings to learn, work, and conduct research. In the field of English language teaching, the cutting-edge research on the Internet of Things-based interactive teaching models is important. The intelligent campus is a new type of campus built aided by advanced techniques such as machine learning and the Internet of Things. In the smart campus, the classroom usually consists of a tangible physical space and an invisible digital space, which can be used to support teaching content through various types of intelligent equipment, promote classroom interaction, and achieve more convenient visualization of educational functions. Based on the initial results of the Internet of Things research, this research establishes a visual education system based on the Internet of Things. At the same time, the Internet of Things is used to study the interactive English teaching mode in order to improve the level of English teaching and thus enhance the technology level of the intelligent campus.
Teaching Method of Japanese Professional Writing Course Based on Big Data Fusion
Authors: Zhao Dandan , Yin Guocai
Published: May 2022

In recent years, the number of Japanese learners has increased year by year. When Japanese is learned as a language, knowledge of the language itself is indispensable. This article aims to explore the teaching methods of Japanese professional writing courses based on the integration of big data. This article first introduces big data fusion and introduces the definition and model of data fusion. Generally, there are two types of data fusion models: distributed and centralized. Then, I analyzed the artificial neural network algorithm, which is a computational model that imitates the animal brain, and then researched the context-based teaching of Japanese professional courses and analyzed the context-based teaching of Japanese professional writing. The results of the context-based Japanese course teaching research show that the average Japanese writing score of the experimental class is 72.7833, the control class score is 66.3333, and the composition fluency scores are 156.27 and 119.73. It can be concluded that the composition performance and composition fluency of students in the experimental class are higher than those in the control class, so educators should let students strengthen vocabulary spelling and memory skills in situational teaching.
Grounded Theory and Social Psychology Approach to Investigating the Formation of Construction Workers’ Unsafe Behaviour
Authors: Han Yu , Li Xuezheng , Feng Zhida , Jin Ruoyu , Kangwa Joseph , Ebohon Obas John
Published: May 2022

There have been limited studies analyzing the causes of construction workers’ unsafe behaviour from the social psychology perspective. Based on a Grounded Theory approach, this study first identified and defined seven coded categories related to workers’ dangerous behaviour on construction sites. The original qualitative data were obtained from individual site interviews conducted with 35 construction professionals. These main categories were found connected to workers’ status of safety awareness and sense of danger, which affected the type of unsafe behaviours, i.e., proactive, passive, or reactive behaviour. By further integrating social cognitive psychology theories into workers’ behavioural decision-making process, the formation mechanism framework and diagram were developed to describe construction workers’ unsafe behaviours based on the dynamic process of balancing the individual desires and perceived safety risks. This study advances the body of knowledge in construction safety behavioural management by performing in-depth theoretical analysis regarding workers’ internal desires, activated by external scenarios and intervened by a personal safety cognition system, which could result in different motivations and various behavioural outcomes. It is argued that safety cognition serves as a mediated moderation system affecting behavioural performance. Practical suggestions on developing a proper safety management system incorporating safety education in guiding construction workers’ site behaviours are presented.
Thermal Straightening Control System for Variable-Section Automotive Leaf Springs Rolling Based on IoT Edge Computing
Authors: Sun Yacan
Published: May 2022

With the rapid development of social economy in recent years, people’s living standards are also improving. The use of automobiles is becoming increasingly frequent, and people’s requirements for the safety, comfort, and energy saving of automobiles are also getting higher. This paper mainly studies the thermal straightening control system after the rolling of variable-section automotive leaf springs through edge computing based on the Internet of Things. This paper presents the basic concepts of IoT edge computing and the role they play in various aspects. The percentage of IoT development trends in 2011 was 6.7%. By 2020, the development trend percentage of IoT reached 68%, an increase of 61.3%. It can be seen that the development of the Internet of Things is very rapid. It can be seen that the straightening accuracy of the thermal straightening control system based on edge computing after the rolling of variable-section automotive leaf springs reaches 78%, and it is 29% higher than the traditional system straightening accuracy, which is only 49%. The safety of the thermal straightening control system of the variable-section automotive leaf spring after rolling based on edge computing reaches 95%, which is 33% higher than the safety of the traditional system. The thermal alignment control system for variable-section automotive leaf springs after rolling based on the edge computing of the Internet of Things is not only safer than the traditional system but also much higher in comfort and alignment accuracy than the traditional system. It can be seen that the thermal straightening control system for variable cross section automotive leaf springs after rolling based on IoT edge computing is more conducive to the development of the automotive industry.
Effects of Comprehensive Nursing Based on Orem’s Self-Care Theory on Symptom Improvement and Pregnancy Outcome in Patients with Antiphospholipid Syndrome: A Retrospective Cohort Study
Authors: Bi Meng , Meng Lingyuan , Bai Liying
Published: May 2022

Objective. A retrospective cohort study was conducted to explore the effects of comprehensive nursing based on Orem’s self-care theory on symptom improvement and pregnancy outcomes in patients with antiphospholipid syndrome (APS). Methods. Sixty patients with antiphospholipid antibody syndrome treated in our hospital from February 2019 to April 2021 were enrolled. The control group received comprehensive nursing, while the study group received comprehensive nursing based on Orem’s self-care theory. Nursing satisfaction, self-nursing ability, anxiety score, social support status, pregnancy outcome, and the score of life quality were compared between the two groups. Results. First of all, we compared the nursing satisfaction, the study group was very satisfied in 23 cases, satisfactory in 5 cases, general in 2 cases, the satisfaction rate was 100.00%. While in the control group, 11 cases were very satisfied, 10 cases were satisfied, 4 cases were general, and 5 cases were dissatisfied, the satisfaction rate was 83.33%. The nursing satisfaction in the study group was higher compared to the control group (

P
<
0.05

). Secondly, the self-concept, sense of self-care responsibility, self-nursing skills, health knowledge, and total score of the study group were higher compared to the control group (

P
<
0.05

). After intervention, the anxiety scores of the two groups decreased. Compared between the two groups, the anxiety scores of the study group before intervention and 1 week, 2 weeks, 3 weeks, and 4 weeks after intervention were lower compared to the control group (

P
<
0.05

). The comparison of social support showed that the scores of objective support, subjective support, utilization of support, and total score of social support in the study group were higher compared to the control group (

P
<
0.05

). The number of abortions in the control group was lower compared to the control group, and the number of full-term deliveries was higher compared to the control group (

P
<
0.05

). Finally, we compared the scores of life quality. After nursing, the scores of life quality of the two groups increased. Of note, the scores of physiological function, psychological function, social function, and health self-cognition in the study group were lower compared to the control group (

P
<
0.05

). Conclusion. Comprehensive nursing for patients with APS based on Orem’s self-care theory can effectively improve clinical symptoms and pregnancy outcome and play a positive role in facilitating patients’ nursing satisfaction and self-nursing ability, which can also effectively strengthen mental health and social support, this nursing model is worth popularizing in clinic.
A Privacy-Aware Electricity Consumption Data Collection Model Based on Group Blind Signature
Authors: Li Fengyin , Li Xiao , Liu Peiyu , Sun Xueqing , Yu Siqi , Ge Junrong
Published: May 2022

Blockchain gives a new method for distributed data ledgering. The smart grid obtains efficient two-way data transmission and information control. It effectively monitors and regulates the grid by collecting real-time electricity consumption data of users. However, online data collection brings privacy leakage. To solve the problem of privacy leakage in the electricity data collection in the smart grid, a privacy-aware electricity data collection model is proposed. Firstly, we propose a new group blind signature scheme by introducing the blind feature into the identity-based encryption method. Secondly, by applying the proposed group blind signature scheme to the electricity data collection process, we propose a privacy-aware electricity data collection model. The proposed model ensures the conditional anonymity and traceability of user identity and the privacy protection and unforgeability of electricity consumption data.
Research on Influencing Factors of Clinical Efficacy of Meniscus Resection Based on Logistic Regression Analysis
Authors: Mao Xiaocheng , Hong Qingnan , You Ruijin , Lu Yizhe , Zhao Feng
Published: May 2022

In order to solve the factors affecting the clinical efficacy of meniscus resection, a method based on logistic regression analysis is proposed. From May 2019 to May 2020, 60 patients with discoid meniscus who underwent arthroscopic surgery in the Joint Department of the Second Hospital of a certain city were selected as the research objects; the surgical methods are divided into partial meniscus excision and plasty and total meniscus resection. The Lysholm function score was used to evaluate the clinical efficacy of arthroscopic surgery for discoid meniscus injuries before and 3, 6, and 12 months after surgery and postoperative application of Ikeuchi score and Tegner exercise ability score to assess age, gender, body mass index (BMI), duration of symptoms, and the influence of meniscus injury types and surgical methods on the efficacy of arthroscopic surgery for discoid meniscus injuries. Experimental results show that Ikeuchi’s assessment of the excellent and good rate of arthroscopic knee joints was significantly higher than that of the control group, the incidence of postoperative pain was significantly lower than that of the control group, and the difference was statistically significant (

P
<
0.05

). Postoperative pain and premature weight-bearing of discoid meniscus injury of knee joint, factors such as noncold compress after operation, articular cartilage damage, age, and time from onset to operation are closely related; the difference was statistically significant (

P
<
0.05

). Postoperative evaluation according to Ikeuchi score: excellent in 38 cases, good in 14 cases, 8 cases were poor, and the excellent and good rate was 86.7%. The patient’s age, type of meniscus tear, and duration of symptoms have a certain impact on the postoperative clinical efficacy of discoid meniscus injury; BMI and surgical methods have no significant impact. Logistic regression analysis results show that postoperative pain and premature weight-bearing of discoid meniscus injury of the knee joint, no cold compress after operation, accompanied by articular cartilage damage, age, and factors such as onset to operation time are closely related; the difference was statistically significant (

P
<
0.05

). It proves that arthroscopic surgery for discoid meniscus injury has the advantages of less damage and faster recovery, it is the first choice for the treatment of discoid meniscus injury, and the postoperative effect is significant in young patients and those with short duration of symptoms; mixed tears have a greater impact on the postoperative recovery of patients with discoid meniscus injury; therefore, patients with discoid meniscus injury should undergo surgery as soon as possible and perform active rehabilitation exercises after the operation.
Exploration on College Ideological and Political Education Integrating Artificial Intelligence-Intellectualized Information Technology
Authors: Li Wenjuan , Liu Fengkai
Published: May 2022

In recent years, with the vigorous development and application of Artificial Intelligence (AI), the application of AI in education is becoming more and more extensive. This study makes a theoretical analysis of AI-Intellectualized Information Technology (IT). Discrete Cosine Transform (DCT)-Based Speech Recognition (SR) and Genetic Algorithm (GA)-Based Image Recognition (IR) are used to analyze the College Ideological and Political Education (IAPE). The research findings prove that the advantages of integrating AI-intellectualized IT on College IAPE outweigh the disadvantages. The improvement of technological development, which accounts for 71.17% of undergraduate gains, is the most significant, and the smallest gain is technology coverage, which is 36.80%. Overall, 57.21% are interested in new technology, and the students’ enthusiasm accounts for 30.77%. Most of the students focus on the innovation performance of technology, accounting for 75.92%. With an average influence of 89.04% on undergraduates, technology has the largest impact, followed by 85.78% on students with masters or higher degrees. The largest impact of diversified teaching methods for all students is 62.48%. This study provides some reference values for AI-intellectualized IT research and analysis, as well as students’ IAPE.
Determination of the Activity Inventory in the Structural Components of the Dalat Nuclear Research Reactor for Its Decommissioning Planning
Authors: Tran Quoc-Duong , Nguyen Kien-Cuong , Luong Ba-Vien , Huynh Ton-Nghiem , Pham Quang-Huy , Vo Doan-Hai-Dang , Nguyen Nhi-Dien
Published: May 2022

This report presents the methods and calculated results of the activity inventory in the structural components of the Dalat Nuclear Research Reactor (DNRR). These components include the shielding concrete, the reactor tank, and its inside irradiated facilities; the thermal and thermalizing columns; and the horizontal channels. The MCNP5 code with a three-dimensional neutron transport model was used to calculate the neutron flux distribution, neutron energy spectrum at different locations, and activation cross sections of long-lived radioactive nuclides in activated major materials, including heavy concrete, reflection graphite, and aluminum of the reactor. The calculated results of the energy spectrum and activation cross sections of MCNP5 were used in the ORIGEN2.1 point depletion code to calculate the neutron-induced activity of activated materials at different time points by modeling the irradiation history and radioactive decay. Radioactivity of long-lived key activation products such as 41Ca, 60Co, 55Fe, 63Ni, and 152Eu was modeled, and volumes of radioactive waste mainly of ordinary concrete, graphite, and aluminum in the structural components of the reactor were estimated. Experimental results of neutron flux and specific activities of some typical nuclides such as 60Co, 152Eu, 55Fe, and 63Ni in activated aluminum samples showed good agreement with the calculated results. As part of the national regulation requirements, the obtained data have been used to develop the decommissioning plan for the operational DNRR, with an estimation of about 10 years before its permanent shutdown.
The Application of Biomechanics Combined with Human Body Structure in Volleyball Technical Analysis
Authors: Jiang Wei , Zhao Kai
Published: May 2022

With the development of volleyball, the development of traditional school volleyball has been paid increasing attention. This has also aroused the concern of schools, coaches, and athletes and has become the focus of volleyball development and reserve talent training. The purpose of this paper is to use the knowledge of biomechanics to study serving technology and attacking technology in volleyball. In the aspect of biomechanics, this paper proposes the finite element modeling theory of the human body. The upper limbs of volleyball players are modeled and analyzed, and four powerful teams are selected for video analysis of volleyball offensive skills. The overall difference between athletes in different groups is very obvious. The phase with the longest time and the greatest difference was the P3 phase, which took 0.802 ± 0.085 seconds.