bluuebunny/crossref_metadata_2025 huggingface dataset:
Wogonoside attenuates liver fibrosis by triggering hepatic stellate cell ferroptosis through SOCS1/P53/SLC7A11 pathway
Authors: Liu Guofang , Wei Can , Yuan Siyu , Zhang Zhe , Li Jiahao , Zhang Lijun , Wang Guokai , Fang Ling
Published: July 2022

Wogonoside (WG) is a flavonoid chemical component extracted from Scutellaria baicalensis, which exerts therapeutic effects on liver diseases. Ferroptosis, a novel form of programmed cell death, regulates diverse physiological/pathological processes. In this study, we attempted to investigate a novel mechanism by which WG mitigates liver fibrosis by inducing ferroptosis in hepatic stellate cells (HSCs). A CCl4‐induced mouse liver fibrosis model and a rat HSC line were employed for in vivo and in vitro experiments, both treated with WG. Firstly, the levels of the fibrotic markers α‐smooth muscle actin (α‐SMA) and α1(I)collagen (COL1α1) were effectively decreased by WG in CCl4‐induced mice and HSC‐T6 cells. Additionally, mitochondrial condensation and mitochondrial ridge breakage were observed in WG‐treated HSC‐T6 cells. Furthermore, ferroptotic events including depletion of SLC7A11, GPX4 and GSH, and accumulation of iron, ROS and MDA were discovered in WG‐treated HSC‐T6 cells. Intriguingly, these ferroptotic events did not appear in hepatocytes or macrophages. WG‐elicited HSC ferroptosis and ECM reduction were dramatically abrogated by ferrostatin‐1 (Fer‐1), a ferroptosis inhibitor. Importantly, our results confirm that SOCS1/P53/SLC7A11 is a signaling pathway which promotes WG attenuation of liver fibrosis. On the contrary, WG mitigated liver fibrosis and inducted HSC‐T6 cell ferroptosis were hindered by SOCS1 siRNA and pifithrin‐α (PFT‐α). These findings demonstrate that SOCS1/P53/SLC7A11‐mediated HSC ferroptosis is associated with WG alleviating liver fibrosis, which provides a new clue for the treatment of liver fibrosis.
Analysis of Wilson‐Hilferty distribution under progressive Type‐II censoring
Authors: Dey Sanku , Elshahhat Ahmed
Published: July 2022

A new re‐parameterize form of the Wilson‐Hilferty distribution for data modelling with increasing, decreasing and bathtub shape hazard rates has been considered. This paper takes into account the estimation for the unknown model parameters, reliability function and hazard function based on two frequentist methods and Bayesian method of estimation using Type‐II progressively censored data. In frequentist method, besides conventional likelihood based estimation, another competitive method, known as maximum product of spacing (MPS) method is proposed to estimate the model parameters, reliability function and hazard function as an alternative approach to the common likelihood method. In Bayesian paradigm, we have also considered the MPS function as an alternative to the traditional likelihood function and both are also discussed under the Bayesian set up for unknown parameters, reliability function and hazard function. Moreover, for all considered unknown quantities, the approximate confidence intervals under the proposed frequentist approaches as well as the Bayes credible intervals are constructed. Extensive Monte‐Carlo simulation studies are conducted to evaluate the performance of the proposed estimates with respect to various criteria quantities. Furthermore, we discuss an optimal progressive censoring plan among different competing censoring plans using three optimality criteria. Finally, to show the applicability of the proposed methodologies in a real‐life scenario, an engineering dataset is analysed.
Designing a longitudinal clinical trial based on a composite endpoint: Sample size, monitoring, and adaptation
Authors: Schoenfeld David A. , Ramchandani Ritesh , Finkelstein Dianne M.
Published: July 2022

Longitudinal clinical trials are often designed to compare treatments on the basis of multiple outcomes. For example in the case of cardiac trials, the outcomes of interest include mortality as well as cardiac events and hospitalization. For a COVID‐19 trial, the outcomes of interest include mortality, time on ventilator, and time in hospital. Earlier work by these authors proposed a non‐parametric test based on a composite of multiple endpoints referred to as the Finkelstein‐Schoenfeld (FS) test (Finkelstein and Schoenfeld. Stat Med. 1999;18(11):1341–1354.). More recently, an estimate of the treatment comparison based on multiple endpoints (related to the FS test) was proposed (Pocock et al. Eur Heart J. 2011;33(2):176–182.). This estimate, which summarized the ratio of the number of patients who fared better vs worse on the experimental arm was coined the win ratio. The aim of this article is to provide guidance in the design of a trial that will use the FS test or the win ratio. The issues that will be considered are the sample size, sequential monitoring, and adaptive designs.
Programmable Assembly of Colloidal Nanoparticles Controlled by Electrostatic Potential Well
Authors: Liu Yuanlan , Wang Yawen , Sun Yinghui , Li Dong , Liang Zhiqiang , Liang Wenkai , Gao Heng , Qin Wei , Qian Hongqiang , Jiang Lin
Published: July 2022

Compared with the individual colloidal nanoparticles, programmable nanoassemblies with well‐defined configurations exhibit more prominent coupling effects and collective behaviors. The full realization of the unique superiority of these nano assemblies requires the development of feasible approaches to assemble colloidal nanoparticles into an organized nanostructure on substrates, which remains a major challenge in nanotechnology at present. Herein, a facile strategy is developed to programmatically design diversified nanostructures through the rational capture of nanoparticles with flexibly adjustable particle types, including their sizes, shapes, or components. Importantly, such a strategy takes advantage of a bowl‐shaped electrostatic potential well that forms based on the combination of a positively charged nanoparticle and a negatively charged substrate, where theory and simulation are employed to reveal the notable role of the substrate potential. As a demonstration, a series of nanostructures with customized geometries and locations have been successfully fabricated, especially the asymmetric dimer structures, which bring about distinct localized surface plasmon resonance hybridization and coupling effects. Therefore, the joint computational–experimental showcase paves the way toward the preparation of ideal nanostructures, providing valuable insight into the development of optical encryption, smart sensing, sensitive bio‐detection, and so on.
Der TK Elevator Testturm in Rottweil – Herausforderungen bei der Ausführung der weltweit höchsten Membranfassade
Authors: Moritz Karsten , Höreth Frank
Published: July 2022

Der vorliegende Beitrag beschreibt einige der Herausforderungen bei der Ausführung der bis dato höchsten Membranfassade der Welt. Denn die Montage der 16.000 m2 großen Membran‐Stahlkonstruktion am nackten Betonschaft bis in eine Höhe von 246 m weicht deutlich vom business as usual im Membranbau ab. Das Unternehmen Taiyo Europe GmbH hat sich gemeinsam mit seiner Auftraggeberin, der Ed. Züblin AG, diesen Herausforderungen gestellt und dabei bautechnisches Neuland betreten.
Hot‐dip galvanizing of high‐strength hot‐finished hollow sections
Authors: Pinger Thomas , Müller Thomas , Kaucke Christoph , Straetmans Boris , Wessel Waldemar
Published: July 2022

The galvanizability of high‐strength, hot‐finished hollow sections was investigated as part of a test programme. Here, square sections made of steel grades ranging from 355 to 620 MPa were galvanized using two processes: a classic, quasi‐rare zinc melt and a zinc‐5 % aluminium alloy. To determine the influence of galvanizing on the material properties, samples were taken from the galvanized specimens, tensile tests and Charpy‐V‐tests were performed on them, and the results were compared with those in the ungalvanized initial state. Furthermore, we investigated the optical and microstructural characteristics of the zinc coatings, as well as possible cracking due to liquid metal embrittlement (LME). The results show that the two galvanizing processes used in the test programme produce no negative effect, but rather tend to have a positive effect on the mechanical properties of the steels tested. In all cases, stable zinc coatings are formed that exhibit the expected characteristics. Cracking as a result of LME could not be detected.
Social capital, information sharing, ambidexterity, and performance for technology park firms in Turkey
Authors: Wasti Syeda Nazli , Terzi Hilal , Kerti Feyza
Published: July 2022

Small and medium‐sized enterprises (SMEs) in uncertain emerging markets tend to pursue exploitation at the expense of exploration. The purpose of this study is to investigate whether social capital can alleviate this imbalance by supporting the firms' ambidexterity, and thus the performance of such firms. Using survey data from high‐tech SMEs in Turkish technoparks, Phase 1 of the study tests a mainstream serial mediation model, where the social capital–performance relationship is mediated by information sharing and ambidexterity dimensions (exploration and exploitation). The results show that rather than merely forming structural social capital linkages, firms also need to develop relational social capital for higher ambidexterity and performance. Phase 2 of the study elaborates on these findings through interviews with 12 technopark firm managers regarding information sharing, collaborations, and innovative activities. The findings in this phase provide strong evidence that low generalized trust in the Turkish context plays an inhibiting role in the process from social capital to firm performance.
Tracheal resection and anastomosis in a dog with an osteochondroma
Authors: Behrens Kristen N. , Turley Kelsey A. , Mouser Pamela J. , Casale Sue A.
Published: July 2022

A 2‐month‐old golden retriever was presented with a history of intermittent wheezing and inspiratory stridor. Previous thoracic radiographs revealed the presence of a discrete opacity partially obscuring the trachea at the level of the thoracic inlet. Through tracheoscopy, a smooth, broad‐based intratracheal mass was visualised just past the thoracic inlet that made up about 80% of the tracheal diameter. Histological examination of biopsies obtained during this procedure was consistent with tracheal osteochondroma. The mass was removed by resection and anastomosis of the trachea through a cervical approach. Histopathology of the excised mass confirmed the prior diagnosis of osteochondroma. Re‐evaluation and repeat thoracic radiographs 6 months postoperatively showed complete resolution of clinical signs and no evidence of recurrent disease. This case demonstrates that tracheal resection and anastomosis can be a viable and curative surgical procedure for some masses, including osteochondromas, within the trachea.
Ten Recommendations for an Effective Model for Regulating Truth in Political Advertising and Conclusion
Authors: Hill Lisa , Douglass Max , Baltutis Ravi
Published: July 2022

We conclude by making ten recommendations in light of the foregoing discussion. These recommendations are intended to ensure that our ideal-type model is capable of fulfilling four general goals; first, it should be acceptable to the public as well as the political class in order to ensure bi- and, ideally, multi-party support; second, it should allow complaints to be handled in a timely manner; third, it should be capable of withstanding constitutional challenge, not only to ensure that it is not invalidated but also that it is not stifling good faith political speech; and fourth, it should be able to deal effectively with the problem of false campaign statements without producing too many unwanted and unintended consequences such as: the cynical use of injunctions against candidates for political purposes; vexatious litigation; the strategic use of false campaign statements with the intention of absorbing the pecuniary penalty as a ‘routine campaign expense’; ‘dragged-out’ litigation; ex-post rulings by the Supreme Court; unjust prosecution; mischievous flooding of trivial litigation for the sole purpose of distracting the Commission from its primary responsibility; and the perception that the regulator is too restrictive in its assessments.
The Effects of False Campaign Statements
Authors: Hill Lisa , Douglass Max , Baltutis Ravi
Published: July 2022

In this chapter we explore the short- and long-term effects of false election information on electoral and other democratic processes from both a theoretical and empirical perspective. We examine the supply and demand side of the mis- and disinformation stories, drawing on the literature in behavioural economics and psychology to explain the underlying mechanisms at play in the demand side (consumers) and the motivations on the supply side (producers). We show that, due to the high stakes and unavoidably competitive nature of modern elections on the one hand, and perverse financial incentives within the information market on the other, election mis- and disinformation will be difficult to combat without a legal remedy.
Disinformation as a Democratic Collective Action Problem or Why a Legal Solution Is Warranted
Authors: Hill Lisa , Douglass Max , Baltutis Ravi
Published: July 2022

In this chapter we explore how false election information violates democratic values; in other words, we examine the extent to which and the manner in which false election information impugns the legitimacy of Australian elections, and in particular, the democratic legitimacy criteria of ‘effective participation’ and ‘enlightened understanding’. These criteria are central pillars of the free speech condition that enables any authentic democracy to function properly. Because there are few incentives to desist from polluting the election information environment and also because of the significant social costs it entails, the problem should be approached as a collective action problem rather than as an issue of individualised rights. This distinction is consistent with jurisprudence on the freedom of political communication implied in the Australian Constitution and endorsed in multiple judgements, as we show in detail in Chapter 5. We conclude this chapter by arguing that compulsory voting places an extra duty on the Australian state to ensure that voting takes place in a relatively clean information environment.
Current Approaches to Combatting the Emerging ‘Infodemic’
Authors: Hill Lisa , Douglass Max , Baltutis Ravi
Published: July 2022

In this chapter we examine how the false election information problem has been managed so far in Australia. Up to this point, mainly non-legislative means, such as fact-checking services, voluntary codes of conduct and civil society remedies have been used. Defamation laws have also been invoked to address the problem and we assess their capacity to perform this function. Although there is value in these alternative methods, we question whether they will be sufficient to adequately combat the problem, particularly in the digital age. We conclude that they should be used in conjunction with the legal solution we propose.
Why Australia Is a Great Place to Start: The Implied Freedom of Political Communication and TIPA Laws
Authors: Hill Lisa , Douglass Max , Baltutis Ravi
Published: July 2022

In this chapter we show that the Australian constitutional and jurisprudential approach to political speech, as embodied in the implied freedom of political communication, makes Australia a uniquely congenial setting for TIPA laws and the type of burden they place on political speech. This is reflected in a range of High Court decisions as well as the fact that the Supreme Court of South Australia has upheld the constitutionality of the South Australian TIPA law based on Australian implied freedom of communication jurisprudence. Our exploration of these decisions and their broader context throws light on how such a freedom is supposed to work and is constituted. Notably, the Courts have achieved a balance in the ‘freedom-fairness’ trade-off, and indicated that they consider TIPA laws, in constraining some political speech, as tipping the scales towards ‘fairness’ without at the same time unduly impacting freedom. We end the chapter by summarising our argument so far.
Implementation of s 113: Lessons to Adopt, Pitfalls to Avoid and Refinements to Pursue
Authors: Hill Lisa , Douglass Max , Baltutis Ravi
Published: July 2022

Because s 113 has been in place for some time it has much to teach us about how to design a viable regime for truth in election advertising. However, in sketching out our preferred or ideal model we offer a number of enhancing modifications to SA’s framework, some of which are inspired by practice (and shortcomings) in other common law jurisdictions. We focus here on the implementation of s 113, in particular on issues associated with: whether the publication of misleading election information should be a civil or criminal matter; timeliness and resources including ergonomic aspects of the investigation process; the notion of ‘material extent’ and its complications in determining a breach of s 113; the issue of possible unintended consequences of TIPA-type legislation; problems associated with determining the difference between purported statements of fact and opinion; legal defences; and appropriate penalties and adjudicators.
Application of Image Recognition in Precise Inoculation Control System of Pleurotus Eryngii
Authors: Meng Xiangxiu , Zhu Xuejun , Ding Yunpeng , Qi Dengrong
Published: July 2022

The traditional inoculation technology of Pleurotus eryngii is artificial inoculation, which has the disadvantages of low efficiency and high failure rate. In order to solve this problem, it is necessary to put forward the automatic control system of Pleurotus eryngii inoculation. In this paper, based on the system of high reliability, high efficiency, flexible configuration and other performance requirements, PLC is used as the core components of the control system and control the operation of the whole system. In order to improve the efficiency of the control system, the particle swarm optimization algorithm was used to optimize the interpolation time of the trajectory of the manipulator. Through simulation, it was found that the joint acceleration curve was smooth without mutation, and the running time was short. Because the position deviation of the Culture medium of Pleurotus eryngii to be inoculated will inevitably occur when it is transferred on the conveyor belt, the image recognition technology is used to accurately locate them. In order to improve the efficiency of image recognition, the genetic algorithm (GA) is used to improve Otsu to find the target region of Culture medium of Pleurotus eryngii to be inoculated, and the simulation results showed that the computational efficiency could be increased by 70%. In order to locate the center of the target region, the mean value method is used to find their centroid coordinates. At last, it is found by simulation that the centroid coordinates could be accurately calculated for a basket of 12 Pleuroides eryngii medium to be inoculated.
A Novel Robust Adaptive Color Image Watermarking Scheme Based on Artificial Bee Colony
Authors: Xiao Tingting , Li Wanshe
Published: July 2022

This paper proposes a new robust adaptive watermarking scheme based on dual-tree quaternion wavelet and artificial bee colony, wherein the host images and watermark images are both color images. Color host images and watermark images in RGB space are transformed into YCbCr space. Then, apply Arnold chaotic map on their luminance components and use the artificial bee colony optimization algorithm to generate embedding watermark strength factor. Dual-tree quaternion wavelet transform is performed on the luminance component of the scrambled host image. Apply singular value decomposition on its low-frequency amplitude sub-band to obtain the principal component (PC). Embed the watermark into the principal component. Analysis and experimental results show that the proposed scheme is better as compared to the RDWT-SVD scheme and the QWT-DCT scheme.
Detection and Location of Myocardial Infarction from Electrocardiogram Signals Using Median Complexes and Convolutional Neural Networks
Authors: Liu Shijie , Bin Guanghong , Wu Shuicai , Zhou Zhuhuang , Bin Guangyu
Published: July 2022

When doctors judge myocardial infarction (MI), they often introduce 12 leads as the basis for judgment. However, the repetitive labeling of nonlinear ECG signals is time-consuming and laborious. There is a need of computer-aided techniques for automatic ECG signal analysis. In this paper, we proposed a new method based on median complexes and convolutional neural networks (CNNs) for MI detection and location. Median complexes were extracted which retained the morphological features of MIs. Then, the CNN was used to determine whether each lead presented MI characteristics. Finally, the information of the 12 leads was synthesized to realize the location of MIs. Six types of MI recognition were performed, including inferior, lateral, anterolateral, anterior, and anteroseptal MIs, and non-MI. We investigated cross-database performance for MI detection and location by the proposed method, with the CNN models trained on a local database and validated by the open PTB database. Experimental results showed that the proposed method yielded F1 scores of 84.6% and 80.4% for the local and PTB test datasets, respectively. The proposed method outperformed the traditional hand-crafted method. With satisfying cross-database and generalization performance, the proposed CNN method may be used as a new method for improved MI detection and location in ECG signals.
Experimental Performance Analysis of Machine Learning Algorithms
Authors: Khekare Ganesh , Turukmane Anil V. , Dhule Chetan , Sharma Pooja , Kumar Bramhane Lokesh
Published: July 2022

Machine Learning models and algorithms have become quite common these days. Deep Learning and Machine Learning algorithms are utilized in various projects, and now, it has opened the door to several opportunities in various fields of research and business. However, identifying the appropriate algorithm for a particular program has always been an enigma, and that necessitates to be solved ere the development of any machine learning system. Let’s take the example of the Stock Price Prediction system, it is used to identify the future asset prediction of a industry or other financial aspects traded on a related transaction. Now, it is a daunting task to find the right algorithm or model for such a purpose that can predict accurate values. There are several other systems such as recommendation systems, sales prediction of a mega-store, or predicting what are the chances of a driver meeting an accident based on his past records and the road they’ve taken. These problem statements require to be built using the most suitable algorithm and identifying them is a necessary task. This is what the system does, it compares a set of machine learning algorithms while determining the appropriate algorithm for the selected predictive system using the required data sets. The objective is to develop an interface that can be used to display the result matrix of different machine learning algorithms after being exposed to different datasets with different features. Besides that, one can determine the most suitable (or optimal) models for their operations, using these fundamentals. For experimental performance analysis several technologies and tools are used including Python, Django, Jupyter Notebook, Machine Learning, Data Science methodologies, etc. The comparative performance analysis of best known five time series forecasting machine learning algorithms viz. linear regression, K – nearest neighbor, Auto ARIMA, Prophet, and Support Vector Machine is done. Stock market, earth and sales forecasting data is used for analysis.
Performance Analysis of Fault Detection Rate in SRGM
Authors: Sun Zhichao , Zhang Ce , Wen Yafei , Fan Miaomiao , Liu Kaiwei , Li Wenyu
Published: July 2022

The fault detection rate is one of the main parameters of the software reliability model. Different forms of fault detection rates have different functions. This paper focuses on the influence of fault detection rate on software reliability, proposes a single reliability model multi-failure data set multi-fault detection rate analysis plan, and analyses the impact of fault detection rate on SRGM. After experimental analysis, the performance of the software reliability model corresponding to the power function and the S-type fault detection rate is better, the performance of the software reliability model corresponding to the constant fault detection rate is acceptable, and the comprehensive performance of the software reliability model corresponding to the exponential fault detection rate is poor. The research in this paper has a certain guiding role in the selection of parameter models in software reliability modelling and the determination of the optimal release time.
Research on Vibration Index of IRI Detection Based on Smart Phone
Authors: Zeng Jingxiang , Zhang Jinxi , Cao Qianqian , Guo Wangda
Published: July 2022

With the development of science and technology, intelligent pavement smoothness detection becomes possible. Intelligent IRI (International Roughness Index) detection is one of the important development directions of pavement performance detection. Different from traditional IRI detection, intelligent IRI detection uses smart phones to collect traffic vibration data. There are many vibration indexes in IRI evaluation unit of driving vibration data, and IRI evaluation can be realized by extracting vibration indexes. In this study, the corresponding relationship between pavement vibration data and IRI is preliminarily proved by driving test. The synthetic vibration acceleration index can reflect the change of IRI. The length of IRI evaluation unit reflects different significance of pavement performance, and the evaluation vibration index extracted is different. When the evaluation unit is short, IRI reflects the local pavement performance of the evaluation unit, and the correlation between the minimum value of vehicle synthetic vibration acceleration and IRI is the best. When the evaluation unit is long, IRI reflects the overall pavement performance of the evaluation unit, and the correlation between the average value of the absolute value of the vehicle synthetic vibration acceleration and IRI is the best.
Research on Universities’ Control of Online Discourse Power in the Period of COVID-19: A Case Study of Shanghai Universities
Authors: Sun Lei , Fu Zhuojing
Published: July 2022

Under the situation of the normalization of the prevention and control of COVID-19, related online public opinion occurs from time to time. University administrators must grasp the right of online discourse to guide the direction of online public opinion and ensure the stability of campus order. This paper analyzes the necessity and feasibility of university administrators to grasp the right of online discourse from the basis of reality, compares two kinds of measures and their combinations through questionnaires and computer simulation experiments: publishing authoritative information and focusing on opinion leaders, argues the effectiveness of these two types of measures, and puts forward specific countermeasure suggestions on this basis.
An Insight into Load Balancing in Cloud Computing
Authors: Tasneem Rayeesa , Jabbar M. A.
Published: July 2022

Cloud Computing has emerged as a High-performance computing model providing on-demand computing resources as services via the Internet. Services include applications, storage, processing power, allocation of resources and many more. It is a pay-per-use model. Despite of providing various services, it is also experiencing numerous challenges like data security, optimized resource utilization, performance management, cost management, Cloud migration and many more. Among all, Load Balancing is another key challenge faced by Cloud. Effective load balancing mechanism will optimize the utilization of resources and improve the cloud performance. Load balancing is a mechanism to identify the overloaded and under loaded nodes and then balance the load by uniformly distributing the workload among the nodes. Various load balancing mechanisms are proposed by various researchers by taking different performance metrics. However existing load balancing algorithms are suffering from various drawbacks. This paper emphasizes the comparative review of various algorithms on Load Balancing along with their advantages, shortcomings and mathematical models.
A Multi-modal Time Series Intelligent Prediction Model
Authors: Xian Qingyu , Liang Wenxuan
Published: July 2022

The power load prediction can ensure the power supply and dispatch, which will be useful for market participants to plan and make strategic decisions to enhance reliability, save operation and maintenance costs. Short-term load data series have obvious approximate periodicity, while long-term load data series show variability and dynamic features. In addition, time series data of various modalities, such as market reports and production management data, could play a role in load prediction. One kind of multi-modal CNN-BiLSTM architecture is proposed to predict short-term and long-term load data, which have an improved shared parameter convolutional network to learn feature representation and an improved attention-based BiLSTM mechanism, which could model the dynamic features of multimodal on time series data. Experimental results on multimodal dataset show that, compared with other baseline systems, this model has some advantages in the prediction accuracy.
Research on the Deployment Strategy of Enterprise-Level JCOS Cloud Platform
Authors: Jiang Jianfeng , An Shumei
Published: July 2022

Ruijie JCOS cloud management platform is the first cloud management platform based on OpenStack principle in China. It has the advantages of stable operation, fast deployment, wide compatibility and high performance. Taking the basic technology of cloud platform management as the core, this paper gives a general description of the deploy of the whole cloud platform, from which we can understand and analyze the shortcomings of building traditional data center, and then illustrate the general process of integrating resources and reducing costs by virtualization technology in combination with real application practice.
A Private Cloud Platform Supporting Chinese Software and Hardware
Authors: Li Man , Wang Zhiqiang , Zhao Jinyang , Ou Haiwen , Chi Yaping
Published: July 2022

This paper designs and implements a private cloud platform deployed on an office system that supports domestic software and hardware. With the rapid development of cloud computing, more and more enterprises and users choose cloud platform as a vital Internet resource. At present, most private cloud technologies rely on mature foreign commercial applications and frameworks, and it isn’t easy to achieve compatibility between Chinese software and hardware. Therefore, it is urgent to design a private cloud platform that supports Chinese software and hardware. The key private cloud technology of the cloud platform designed in this paper is the key technology of private cloud that supports independent and controllable Chinese software and hardware. The cloud platform uses virtual computing, virtual storage, virtual network, and other technologies to complete the virtualization of computing resources, storage resources, and network resources. Users can centrally schedule and manage virtual resources.
Gait Planning of a Quadruped Walking Mechanism Based on Adams
Authors: Gao Gangyi , Ling Hao , Ou Cuixia
Published: July 2022

In this paper, the kinematics analysis and gait planning of quadruped walking mechanism are carried out. Firstly, a simplified four-legged mechanism model is established; then the kinematics of the walking mechanism is analyzed; On this basis, the gait planning of walking mechanism is studied, the forward motion (four step movement) gait is analyzed, the corresponding leg swing order of each gait is calculated; Finally, ADAMS software is used to simulate and analyze the gait planning.
Design and Implementation of Full Adder Circuit Based on Memristor
Authors: Tang Ning , Wang Lei , Xia Tian , Wu Weidong
Published: July 2022

In order to break through the traditional von Neumann architecture of computing and memory cell separation and speed up the computing speed, it is necessary to realize in memory computing, and memristor is an excellent carrier to realize in memory computing. Then, the development, principle, characteristics and application prospect of memristor are briefly introduced, and the characteristic curve of memristor is obtained by simulating the model of memristor. The principle and characteristics of memristor are explained more intuitively. Then, based on the memory resistor, the simple logic circuit design principle is described. The logic structure can be realized by using the memory resistor as the calculation element and adding a CMOS inverter, so as to realize the simple logic circuit. The paper designs the simple logic circuit including gate, gate, or gate by spice software, and simulates the circuit of gate, gate, gate, or gate. Then, based on the above logic gate, the circuit design of adder is carried out, the circuit diagram and design scheme are given, and the simple description and SPICE simulation are given. The design scheme is reviewed and summarized, its advantages and disadvantages are analyzed, and the optimization and improvement scheme is proposed.
Design of Intelligent Recognization System Architecture Based on Edge Computing Technology
Authors: Guo Lejiang , Xiao Lei , Chen Fangxin , Tu Wenjie
Published: July 2022

With the increasing acceleration of 5G network construction, artificial intelligence, Quantum technology, edge computing provides content distribution and storage computing services near the network edge which greatly reducing the delay of data processing and service delivery. Starting with the process of information support and decision planning, it analyzes the relationship between edge computing, Quantum and the massive military data. It puts forward an intelligence system architecture design based on edge computing and Quantum. Combined with the openness and flexibility of the system architecture, this paper realizes the mix between data platform and data. It realizes the connection with the existing intelligence system which improves the efficiency of existing data and expands the scenario of edge computing.
Multi-objective Reliability Optimization of a Pharmaceutical Plant by NSGA-II
Authors: Chebouba Billal Nazim , Mellal Mohamed Arezki , Adjerid Smail
Published: July 2022

This work addresses the use of a MO optimization algorithm to deal with the reliability optimization problem in order to determine the redundancy and reliability of each component in the system. Often, these problems are formulated as a single-objective problem with mixed variables (real-integer) and is subject to various design constraints. Classical solution approaches were limited to deal with these problems and most recent solution approaches are based on nature-inspired optimization algorithms which belong to artificial intelligence (AI). In the present paper, the problem is solved as a MO optimization problem through the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to generate the set of optimal solutions, also called Pareto. The latter helps the decision-maker. The case studied consists of a pharmaceutical plant.
Construction of SDN Network Management Model Based on Virtual Technology Application
Authors: Shu Zhong , Deng Boer , Tian Luo , Duan Fen , Sun Xinyu , Chen Liangzhe , Luo Yue
Published: July 2022

This paper designs a virtual SDN network management model constrained by fair and equal network management information access mechanisms by analyzing the problems existing in the universality of existing SDN network management models. Starting with the three-tier structure of the SDN network management system, the main parameters involved in the network management service function, information processing and transmission channel construction in the system were strictly and normatively defined. The design of virtual nodes is regarded as the core element of the network management system, and the information transmission inside it adopts logical operation; The network management service function and the channel for realizing the network management service function are isolated, and the iterative search, analysis and update mechanism is enabled in the network management information transmission channel. By constructing the experimental verification platform and setting the evaluation parameters of the system performance objectives, the scalability and timeliness of the model were evaluated from two aspects: the deployment of network virtual nodes and the dynamic control of network management information channels. The collected experimental core evaluation parameters, the realization time of the network management service function, can show that the dynamic distribution mechanism of network management information can be cross-applied to each virtual node, and the channel update mechanism of network management information can adjust the information processing queue in real-time. The network management system model that has been built realizes the separation of management and control of the network management system and has the characteristics of independent operation, autonomous function, self-matching, rapid deployment and dynamic expansion.
External Information Security Resource Allocation with the Non-cooperation of Multiple Cities
Authors: Li Jun , Cheng Dongsheng , Xing Lining , Tan Xu
Published: July 2022

The external information security resource allocation method is proposed considering the non-cooperation of multiple cities. In this method, the effects of different influence factors, for example, city size, probability of intrusion by illegal users and propagation probability of one-time intrusion on resource allocation is explored. Through the simulation experiment, the proposed conclusions are conveniently and clearly verified.
FSTOR: A Distributed Storage System that Supports Chinese Software and Hardware
Authors: Lin Yuheng , Wang Zhiqiang , Zhao Jinyang , Chen Ying , Chi Yaping
Published: July 2022

In order to develop a distributed storage system that adapts to Chinese software and hardware, build a cloud computing platform that is independently usable, safe and reliable, data utilization is more concentrated and intelligent, and service integration is more unified and efficient. This paper designed and implemented a distributed storage system that supports Chinese software and hardware, which is compatible with Chinese mainstream CPU, operating system, database, middleware and other software and hardware environments. After a lot of experiments and tests, it is confirmed that the system has high availability and high reliability.
Joint Calibration Based on Information Fusion of Lidar and Monocular Camera
Authors: Zheng Li , Peng Haolun , Liu Yi
Published: July 2022

To solve the problem of joint calibration in multi-sensor information fusion, a joint calibration technique based on three-dimensional lidar point cloud data and two-dimensional gray image data is proposed. Firstly, by extracting the corner information of the gray image data, the two-dimensional coordinates of the corner were obtained, and the calibration of the monocular camera was completed by using the corner information, and its internal and external parameters were obtained. Then, by extracting the corner information of the point cloud data obtained by lidar, the corresponding corner points are matched. Finally, the rotation and translation matrix from lidar coordinate system to image coordinate system is generated to realize the joint calibration of lidar and camera.
PCCP: A Private Container Cloud Platform Supporting Domestic Hardware and Software
Authors: Wang Zhuoyue , Wang Zhiqiang , Zhao Jinyang , Chi Yaping
Published: July 2022

With the widespread use of container cloud, the security issue is becoming more and more critical. While dealing with common security threats in cloud platforms and traditional data centres, there are some new security issues and challenges in the container cloud platform. For example, there are significant challenges in network isolation and resource management. This paper proposes a private container cloud platform PCCP based on Docker supporting domestic software and hardware to solve these security problems. This paper introduces the system architecture and functional architecture of the platform. The system has been tested and confirmed to have high availability and high reliability. The platform gives full play to the value of domestic software and hardware and is better able to serve the information construction of our country.
From Data Literacy to Co-design Environmental Monitoring Innovations and Civic Action
Authors: Happonen Ari , Wolff Annika , Palacin Victoria
Published: July 2022

SENSEI is an environmental monitoring initiative run by Lappeenranta University of Technology (LUT University) and the municipality of Lappeenranta in south-east Finland. The aim was to collaboratively innovate and co-design, develop and deploy civic technologies with local civics to monitor positive and negative issues. These are planned to improve local’s participation to social governance issues in hand. These issues can be e.g. waste related matters like illegal dumping of waste, small vandalism into city properties, alien plant species, but on the other hand nice places to visits too. This publication presents initiatives data literacy facet overview, which is aimed at creating equitable access to information from open data, which in turn is hoped for to increase participants motivation and entrepreneurship like attitude to work with the municipals and the system. This is done by curating environmental datasets to allow participatory sensemaking via exploration, games and reflection, allowing citizens to combine their collective knowledge about the town with the often-complex data. The ultimate aim of this data literacy process is to enhance collective civic actions for the good of the environment, to reduce the resource burden in the municipality level and help citizens to be part of sustainability and environmental monitoring innovation activities. For further research, we suggest follow up studies to consider on similar activities e.g. in specific age groups and to do comparisons on working with different stage holders to pin point most appropriate methods for any specific focus group towards collaborative innovation and co-design of civic technologies deployment.
Information Security Resource Allocation Using Evolutionary Game
Authors: Li Jun , Cheng Dongsheng , Xing Lining , Tan Xu
Published: July 2022

Based on the discussion of related concepts and technical theories, the information security resource allocation influencing factors index system is constructed from four aspects: resources, threat sources, vulnerabilities and security measures. With the further analysis of information security factors and their affecting mechanisms, the basic theoretical framework of information security resource allocation is established based on the evolutionary game. Under this framework, the subject relationship in various situations is analyzed. This research work can conduct a reasonable allocation of resources related to information security.
Design of Multi-channel Pressure Data Acquisition System Based on Resonant Pressure Sensor for FADS
Authors: Fan Xianguang , Mao Hailing , Zhu Chengxiang , Wu Juntao , Xu Yingjie , Wang Xin
Published: July 2022

Resonant pressure sensors have high accuracy and are widely used in meteorological data acquisition, aerospace and other fields. The design and experiment of multi-channel pressure data acquisition system based on resonant pressure sensor, which used for the flush air data sensing(FADS) system, are described. The hardware architecture of DSP and FPGA is applied to the data acquisition system. The digital cymometer and 16-bit analog-to-digital converter are used to measure the output signal of the sensor. It is shown the data acquisition system has favourable performance within the operating temperature range. The maximum experimental error is less than 0.02%FS over the range 2–350 kPa. The period of sampling and fitting is less than 8 ms. The frequency and voltage measurements meet accuracy requirements. The calculated pressure and standard pressure result appears excellent linearity, which reach up to 0.9999.
Research on the Design of Community Residential Space from the Perspective of Digitization
Authors: Gao Chenglin , Tong Shuo
Published: July 2022

The residential architecture in the process of urban digital development has become a living complex with real and virtual mirrors, in which people are the unity of connection between spatial environment, identity and living relationship. In this paper, the new value orientation of community residential design is analyzed by sorting out the meaning of community; within the design system of residential space, the intimacy and public consciousness of residents’ neighborhood relationship is enhanced through spatial transition and cultivation of shared living space. The argument is developed from three levels: individual residents’ self-reconstruction, residents’ new behavioral decisions, and spatial behavioral output. Through a series of argumentation, the relationship between community and residential space planning and design is explored, and the data on the interaction between users, usage behavior and space usage of different households are statistically obtained. At the same time, this paper simulates and designs the community residential space module system based on this data and combined with the computer 3D model derivation. The residential block formed by the combination of the smallest modules, as the smallest residential unit, continues to form the design path of a sustainable residential system through the process of combination and deformation of space.
A User-Interaction Parallel Networks Structure for Cold-Start Recommendation
Authors: Lin Yi
Published: July 2022

The goal of the recommendation system is to recommend products to users who may like it. The collaborative filtering recommendation algorithm commonly used in recommendation systems needs to collect explicit/implicit feedback data, and new users do not leave behavioral data on the product, which leads to cold-start problem. This paper proposes a parallel network structure based on user interaction, which extracts features from user interaction information, social media information, and comment information and forms a matrix. The graph neural network is introduced to extract high-level embedded correlation features and the role of parallelism is to reduce computing cost further. Experiments based on standard data sets prove that this method has a certain degree of improvement in NDCG and HR indicators compared to the baseline.