共查询到20条相似文献，搜索用时 15 毫秒
1.
Abdulaziz Attaallah Sabita Khatri Mohd Nadeem Syed Anas Ansar Abhishek Kumar Pandey Alka Agrawal 《计算机系统科学与工程》2021,37(3):313-329
A significant increase in the number of coronavirus cases can easily be noticed in most of the countries around the world. Inspite of the consistent preventive initiatives being taken to contain the spread of this virus, the unabated increase in the cases is both alarming and intriguing. The role of mathematical models in predicting and estimating the spread of the virus, and identifying various preventive factors dependencies has been found important and effective in most of the previous pandemics like Severe Acute Respiratory Syndrome (SARS) 2003. In this research work, authors have proposed the Susceptible-Infectected-Removed (SIR) model variation in order to forecast the pattern of coronavirus disease (COVID-19) spread for the upcoming eight weeks in perspective of Saudi Arabia. The study has been performed by using SIR model with a proposed simplification using average progression for further estimation of β and γ values for better curve fittings ratios. The predictive results of this study clearly show that under the current public health interventions, there will be an increase in the COVID-19 cases in Saudi Arabia in the next four weeks. Hence, a set of strong health primitives and precautionary measures are recommended in order to avoid and prevent the further spread of COVID-19 in Saudi Arabia. 相似文献
2.
Rashed M. Al Thawwad 《通讯和计算机》2009,6(7):57-67
In the development and sustenance of a community, state, or nation, the advancement of technology is vital for survival; here, the need for technology transfer arises and becomes a critical landmark. There are adapting factors in the process of technology transfer that must be addressed to ensure successful technological developments and their continued progress and sustainability. Focused on the successful transfer of sustainable technology to Saudi Arabia, a methodology of measuring physical environments, cultural and infrastructural support, and geographical locations was thoroughly researched and developed. Using a survey instrument based on questions derived from available literature on factors affecting technology transfer, data was collected from private manufacturing industries in Saudi Arabia. Data analysis included person-product-moment correlations and simultaneous regression. The hypotheses were tested at the 0.05 level of significance. In summary, the results indicated that culture, physical environment, and geographical location all have significant effects on technology transfer; necessary accommodations for these adapting factors then become vital to the success of technology transfer and will strongly facilitate the effectiveness of the technology. 相似文献
3.
There are three major issues, among others, associated with the rapid adoption of information technology in Saudi Arabia. These are the changes in online socializing (through Social Media), the information seeking behavior, and the eLearning developments in the local academic institutions. In this causal exploratory research study the main idea was to find the effect of the changes of the former on the latter two. Saudi Arabia is the geographic scope of the study as the most important and influential country in the region. A pre-tested and moderated questionnaire, administered both on- and offline, was used to gather the relevant data. Findings indicate a shift from the conventional to the online information seeking behaviors and a preference of a blended educational system, both traditional (classroom) and eLearning or similar, despite the deep and dramatic penetration of social media in the country that could lead to the false assumption that the local population, especially young people, would turn their back on the conventional education processes. 相似文献
4.
This paper presents a data-based simple model for fitting the available data of the Covid-19 pandemic evolution in France. The time series concerning the 13 regions of mainland France have been considered for fitting and validating the model. An extremely simple, two-dimensional model with only two parameters demonstrated to be able to reproduce the time series concerning the number of daily demises caused by Covid-19, the hospitalizations, intensive care and emergency accesses, the daily number of positive tests and other indicators, for the different French regions. These results might contribute to stimulate a debate on the suitability of much more complex models for reproducing and forecasting the pandemic evolution since, although relevant from a mechanistic point of view, they could lead to nonidentifiability issues. 相似文献
5.
High noise exposure is anticipated to be present in the aircraft maintenance operations in civil aviation sector. The objective of the present study is the assessment of noise exposure and hearing threshold of the aircraft maintenance workers in this sector. Noise levels were measured in the aircraft hangers and in the workshops at a main international airport in Saudi Arabia. Two hundred aircraft maintenance workers were subjected to pure tone audiometry. The average Leq,8h at most of the aircraft maintenance operations was considerably high and most of the workers (89.5%) were exposed to noise levels ≥85 dBA. Frequency analysis of sound pressure levels revealed that the contribution of the octave bands 1, 2 and 4 kHz to the overall noise level was high. The audiograms of the examined workers showed significant hearing impairment as compared to non-noise-exposed Saudi employees. Although the observed excessive noise levels can cause hearing loss, the effect among the studied aircraft maintenance workers was mild. This might be attributed to the usage of hearing protection devices, the intermittent nature of the workers' exposure to noise and job rotation. Statistical analysis revealed significant association of both age and usage of hearing protectors with hearing loss. The effect of exposure duration on hearing loss was also detected. 相似文献
6.
Extant research has focused on monitoring the behaviour of people who use mobile banking (MB) but it has paid little attention to understanding the impact of information technology usage behaviour due to cultural differences. Humans are the weakest link in information technology adoption; past research has shown that not all users are predisposed to change their behaviour radically and adopt new channels of banking. This paper examines the demographic patterns of users and non-users of MB. The paper also investigates the attitudinal influences of users and non-users of MB based on innovation attributes. Using empirical research, the study identifies constructs of innovation attributes that were perceived to be significantly different among the users and non-users of MB. The study provides valuable insights into MB in Saudi Arabia that have not been previously investigated. From a practical point, findings of this study will be particularly useful to banks, financial institutions and telecommunication service providers. 相似文献
7.
自2019年末以来, 全球蔓延的新型冠状病毒(Coronavirus disease 2019, Covid-19)已经给世界人民造成了严重的健康威胁. 其中新型冠状病毒患者的计算机断层扫描(Computer tomography, CT)图像通过肺炎病灶分割技术可以为医学诊断提供有价值的量化信息. 虽然目前基于深度学习的方法已经在新型冠状病毒肺炎病灶分割任务上取得了良好的效果, 但是在面对不同中心数据的情况下分割效果往往会大幅下降. 因此, 研究一种具有更好泛化性能的新型冠状病毒肺炎病灶分割算法具有重要意义. 提出一种新冠肺炎病灶多模型融合分割方法. 通过训练3DUnet模型和2DUnet结合方向场(Direction field, DF)模型, 利用多种模型各自优点进行分割结果的融合, 得到更好的泛化性能. 通过同中心和跨中心数据集的实验, 证明该方法能够有效提高新冠肺炎病灶分割的泛化性能, 为医学诊断分析提供帮助. 相似文献
8.
Aleksandra Stevanović Radoslav Božić Slaviša Radović 《Journal of Computer Assisted Learning》2021,37(6):1682-1693
9.
Abdullah Ismetoglu;Yavuz Canbay; 《SECURITY AND PRIVACY》2024,7(6):e434
Covid-19 is a highly infectious respiratory disease that spreads quickly between individuals and has been recognized as a pandemic by the World Health Organization (WHO). Chest x-ray images, lung computed tomography images, and polymerase chain reaction tests are generally used to diagnose this disease by the doctors. Nevertheless, manual diagnosis of Covid-19 disease is laborious and requires highly experienced professionals. Therefore, automated systems are always needed to assist doctors in their diagnostic decisions. In the field of medicine and healthcare, artificial intelligence and deep learning currently offer incredibly effective and rapid automatic decision-support systems. Since sensitive data is used to diagnose Covid-19, privacy has become a major concern in research that uses artificial intelligence and deep learning. In order to eliminate these issues, this paper proposes a novel deep learning model that privately detects Covid-19 disease. The proposed model utilizes differential privacy technique to provide data privacy and convolutional neural network to diagnose Covid-19 disease. The performance of the proposed model was evaluated through experiments conducted on five different datasets, resulting a maximum accuracy rate of 97%. 相似文献
10.
约简是知识发现的重要过程。经典的基于等价关系的粗糙集理论,没有考虑系统取值的序值性,并且对数据噪声较为敏感。提出了一个基于spearman秩相关分析的序值决策系统约简方法,该方法通过各属性对被决策个体的spearman秩次的影响来确定约简结果。实验结果表明,该方法不但考虑了系统属性值的序值关系,并且对数据噪声不敏感,因而更符合实际应用的要求。 相似文献
11.
Anna Nagurney Mojtaba Salarpour June Dong 《International Transactions in Operational Research》2022,29(1):226-258
In this paper, we develop a unified variational inequality framework in the context of spatial price network equilibrium problems that handles multiple products with multiple demand and supply markets in multiple countries as well as multiple transportation routes. The model incorporates a plethora of distinct trade measures, which is particularly important in the pandemic, as PPEs and other essential products are in high demand, but short in supply globally. In the model, product flows as well as prices at the supply markets and the demand markets in different countries are variables that allows us to seamlessly introduce various trade measures, including tariffs, quotas, as well as price floors and ceilings. Qualitative properties are analyzed. Numerical examples are provided to illustrate the impacts of the trade measures on equilibrium product path and link flows, and on prices, and demand and supply quantities. Given the relevance of the trade measures in the world today and discussions concerning the impacts, the framework constructed in this paper is especially timely. 相似文献
12.
Muhterem Dindar Anna Suorsa Jan Hermes Pasi Karppinen Piia Näykki 《Journal of Computer Assisted Learning》2021,37(6):1553-1565
Covid-19 pandemic has caused a massive transformation in K-12 settings towards online education. It is important to explore the factors that facilitate online teaching technology adoption of teachers during the pandemic. The aim of this study was to compare Learning Management System (LMS) acceptance of Finnish K-12 teachers who have been using a specific LMS as part of their regular teaching before the Covid-19 pandemic (experienced group) and teachers who started using it for emergency remote teaching during the pandemic (inexperienced group). Based on the Unified Theory of Acceptance and Use of Technology framework, a self-report questionnaire was administered to 196 teachers (nexperienced = 127; ninexperienced = 69). Our findings showed no difference between the two groups of teachers in terms of performance expectancy, effort expectancy, LMS self-efficacy and satisfaction. However, the experienced group had higher behavioural intention to use LMS in the future, reported receiving higher online teaching support and displayed higher online teaching self-efficacy in terms of student engagement, classroom management, instructional strategies and ICT skills. For the experienced group, the most significant predictor of satisfaction with LMS was performance expectancy whereas for the inexperienced group, it was the effort expectancy. In terms of behavioural intention to use LMS in the future, the most significant predictor was the performance expectancy for both groups. Further, support was also a significant predictor of behavioural intention for the inexperienced group. Overall, our findings indicate that teachers should not be regarded as a unified profile when managing technology adoption in schools. 相似文献
13.
Convolution Neural Networks (CNN) can quickly diagnose COVID-19 patients by analyzing computed tomography (CT) images of the lung, thereby effectively preventing the spread of COVID-19. However, the existing CNN-based COVID-19 diagnosis models do consider the problem that the lung images of COVID-19 patients in the early stage and incubation period are extremely similar to those of the non-COVID-19 population. Which reduces the model’s classification sensitivity, resulting in a higher probability of the model misdiagnosing COVID-19 patients as non-COVID-19 people. To solve the problem, this paper first attempts to apply triplet loss and center loss to the field of COVID-19 image classification, combining softmax loss to design a jointly supervised metric loss function COVID Triplet-Center Loss (COVID-TCL). Triplet loss can increase inter-class discreteness, and center loss can improve intra-class compactness. Therefore, COVID-TCL can help the CNN-based model to extract more discriminative features and strengthen the diagnostic capacity of COVID-19 patients in the early stage and incubation period. Meanwhile, we use the extreme gradient boosting (XGBoost) as a classifier to design a COVID-19 images classification model of CNN-XGBoost architecture, to further improve the CNN-based model’s classification effect and operation efficiency. The experiment shows that the classification accuracy of the model proposed in this paper is 97.41%, and the sensitivity is 97.61%, which is higher than the other 7 reference models. The COVID-TCL can effectively improve the classification sensitivity of the CNN-based model, the CNN-XGBoost architecture can further improve the CNN-based model’s classification effect. 相似文献
14.
Kate Cochrane Flora Cornish Annette Murphy Neil Denton Louise Bracken 《突发事故与危机管理杂志》2023,31(2):185-197
Crises do not affect populations equally but expose and exacerbate long-standing vulnerabilities and inequalities. Recovery language such as ‘build back better’, or ‘bounce forward’ has been criticised for neglecting underlying inequalities. This paper reports on the process and early outcomes of an inclusive Community Recovery Planning process for the Falkland Islands, in response to Covid-19. The Falkland Islands is home to a complex community, with close ties and short power distances (due to its small size and remoteness), with differences institutionalised in citizenship statuses and entitlements, and shaped by geopolitical tensions. We aimed to use the ‘pandemic as a portal’, seeking out previously ‘less heard’ voices, to make visible previously hidden impacts, and initiate incremental systemic change to tackle them. Community Impact Assessments evidenced specific areas of vulnerability (e.g., housing and income insecurity) and inequalities, largely shaped by differing citizenship status. In tandem with other government currents, the Community Recovery Planning process has contributed to progressive policy changes in Equalities legislation and Income Support. We offer this paper as a demonstration of our methodology for inclusive recovery planning that could be adapted elsewhere. We argue that the inclusion of previously unheard voices contributed to incremental systemic change to reduce inequalities. 相似文献
15.
郭贤海 《计算机测量与控制》2019,27(9):71-75
传统的温湿度控制系统在控制饲料配方所处环境温度和湿度时,很难在短时间内达到标准值,控制过程波动较大。针对上述问题,基于CPLD芯片设计了一种新的温湿度控制系统,系统硬件结构中的传感器选用SH11传感器,利用CLPD芯片校对已经得到的温度信号和湿度信号,通过2个按键和多个接口设置系统网关,引用SS14设置控制电路,结合继电器调节温度和湿度。在IAR开发平台上使用C语言和汇编语言编写了传感器采集节点程序、控制节点程序和网关程序。为检测系统效果,与传统控制系统进行实验对比,结果表明,基于CPLD芯片设计的温湿度控制系统能够在短时间内将饲料配方所处环境温度和湿度调节到标准值附近,控制过程波动小,更适合饲料配方的生产和存储。 相似文献
16.
Notwithstanding the discovery of vaccines for Covid-19, the virus's rapid spread continues due to the limited availability of vaccines, especially in poor and emerging countries. Therefore, the key issues in the present COVID-19 pandemic are the early identification of COVID-19, the cautious separation of infected cases at the lowest cost and curing the disease in the early stages. For that reason, the methodology adopted for this study is imaging tools, particularly computed tomography, which have been critical in diagnosing and treating the disease. A new method for detecting Covid-19 in X-rays and CT images has been presented based on the Scatter Wavelet Transform and Dense Deep Neural Network. The Scatter Wavelet Transform has been employed as a feature extractor, while the Dense Deep Neural Network is utilized as a binary classifier. An extensive experiment was carried out to evaluate the accuracy of the proposed method over three datasets: IEEE 80200, Kaggle, and Covid-19 X-ray image data Sets. The dataset used in the experimental part consists of 14142. The numbers of training and testing images are 8290 and 2810, respectively. The analysis of the result refers that the proposed methods achieved high accuracy of 98%. The proposed model results show an excellent outcome compared to other methods in the same domain, such as (DeTraC) CNN, which achieved only 93.1%, CNN, which achieved 94%, and stacked Multi-Resolution CovXNet, which achieved 97.4%. The accuracy of CapsNet reached 97.24%. 相似文献
17.
介绍了一种以32位微控制器AT32UC3A0512为核心的温湿度检测仪的设计方法。该检测仪采用已校准数字输出信号的数字温湿度传感器DHT11,采集温湿度参数,将所测得的结果在LCD TG12864E上进行实时显示,并利用Zig-Bee技术进行数据传输。 相似文献
18.
通过对湿敏电阻器的特性分析,找出湿敏电阻阻值随温度的指数变化关系,采用附加对数运算电路进行硬件补偿,使其脱离指数状态,低湿性能得到改善;基于EE06型高分子湿敏电容器特性的研究分析,分别在0℃以上和0℃以下分段采用数学模型拟合的软件算法进行温度补偿,使湿敏元件的测湿方程的显著度分别为5 668.579 0和2 416.919 00,均大于F0.01(9,8),在0.01显著水平上是高度显著的。2种温度补偿措施都使湿敏元件的测湿准确度大大提高。 相似文献
19.
During the last few decades in the handling of ongoing crises and preparing for future crises, governments and other public authorities increasingly emphasize the important role religious organizations can play in crises and disaster management. Considering this development, it is appropriate to ask whether the expectations by policymakers are mirrored by the religious organizations themselves? This article aims to answers this question by studying both the organizations' desired role in time of national crises and disasters and the actual role taken by local congregations in Sweden during the Covid-19 pandemic. It also aims to study whether this differs in relation to organizational differences and religious affiliation. The study clearly shows that 8 out of 10 congregations believe they have an important role to play in the event of a disaster or crisis. However, despite the high level of willingness, the role congregations take may not always mirror the governments expectations. In terms of differences between congregations, although cross-religious differences are noted, the size of the organization is the critical factor. The article concludes by discussing the disparity between policymakers' expectations and the willingness of organizations as well as the complexity of policymakers assuming that non-profit organizations will help unequivocally. 相似文献
20.
With the outbreak of Covid-19, both people's health and the world economy are facing great challenges. Contact tracing scheme based on Bluetooth of smartphones has been regarded as a viable way to mitigate the spread of Covid-19. The existing schemes mainly belong to the centralized or the decentralized structure, both of which have their own limitations. It is infeasible for the existing schemes to balance the different demands of governments and users for user privacy and tracing efficiency at different periods of the epidemic. In this paper, we propose a hybrid contact tracing scheme named MLCT (multi-level contact tracing scheme) which is mainly based on short group signature. MLCT provides multiple privacy levels by applying anonymous credential technology and secret sharing technology to desensitize user identity privacy and encounter privacy. Comparing to the previous schemes, MLCT fully considers the different demands of the government, patients, and close contacts for user privacy and tracing efficiency in the different stages of Covid-19. The experimental results show viability in terms of the required resource from both server and mobile phone perspectives. And the security analysis demonstrates that MLCT can achieve the five targets security goals. It is expected that MLCT can contribute to the design and development of contact tracing schemes. 相似文献