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A case-study to examine doctors' intentions to use IoT healthcare devices in Iraq during COVID-19 pandemic 在2019冠状病毒病大流行期间,研究医生在伊拉克使用物联网医疗设备的意图的案例研究
Pub Date : 2020-11-09 DOI: 10.1108/ijpcc-10-2020-0175
Ameer Alhasan, L. Audah, Ishaq Ibrahim, Ammar Al-Sharaa, Ali Saadon Al-Ogaili, Jabiry M. Mohammed
PurposeSeveral countries have been using internet of things (IoT) devices in the healthcare sector to combat COVID-19. Therefore, this study aims to examine the doctors’ intentions to use IoT healthcare devices in Iraq during the COVID-19 pandemic.Design/methodology/approachThis study proposed a model based on the integration of the innovation diffusion theory (IDT). This included compatibility, trialability and image and a set of exogenous factors such as computer self-efficacy, privacy and cost into the technology acceptance model comprising perceived ease of use, perceived usefulness, attitude and behavioral intention to use.FindingsThe findings revealed that compatibility and image of the IDT factors, have a significant impact on the perceived ease of use, perceived usefulness and behavioral intention, but trialability has a significant impact on perceived ease of use, perceived usefulness and insignificant impact on behavioral intention. Additionally, external factors such as privacy and cost significantly impacted doctors’ behavioral intention to use. Moreover, doctors’ computer self-efficacy significantly influenced the perceived ease of use, perceived usefulness and behavioral intention to use. Furthermore, perceived ease of use has a significant impact on perceived usefulness and attitude, perceived usefulness has a significant impact on attitude, which, in turn, significantly impacting doctors' behavior toward an intention to use.Research limitations/implicationsThe limitations of the present study are the retractions of the number of participants and the lack of qualitative methods.Originality/valueThe finding of this study could benefit researchers, doctors and policymakers in the adaption of IoT technologies in the health sectors, especially in developing counties.
一些国家一直在医疗保健领域使用物联网(IoT)设备来抗击COVID-19。因此,本研究旨在研究医生在2019冠状病毒病大流行期间在伊拉克使用物联网医疗设备的意图。设计/方法/途径本研究提出了一个基于创新扩散理论(IDT)整合的模型。这包括兼容性、可试用性和形象,以及一系列外生因素,如计算机自我效能、隐私和成本,纳入技术接受模型,包括感知易用性、感知有用性、态度和行为使用意图。结果发现,兼容性和形象因素对感知易用性、感知有用性和行为意图有显著影响,但可试性对感知易用性、感知有用性有显著影响,对行为意图的影响不显著。此外,隐私、成本等外部因素显著影响医生的使用行为意愿。此外,医生的电脑自我效能显著影响感知易用性、感知有用性和行为使用意愿。感知易用性对感知有用性和态度有显著影响,感知有用性对态度有显著影响,态度对医生的意向使用行为有显著影响。研究的局限性/启示本研究的局限性是参与者数量的撤回和缺乏定性方法。这项研究的发现可以使研究人员、医生和政策制定者在卫生部门,特别是在发展中国家采用物联网技术。
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引用次数: 28
How optimistic do citizens feel about digital contact tracing? - Perspectives from developing countries 公民对数字接触者追踪有多乐观?-发展中国家的观点
Pub Date : 2020-11-06 DOI: 10.1108/ijpcc-10-2020-0166
S. Praveen, Rajesh Ittamalla, Dhilip Subramanian
PurposeDespite numerous positive aspects of digital contact tracing, the implied nature of contact tracing is still viewed with skepticism. Those in favor of contact tracing often undermine various risks involved with it, while those against it often undermine its positive benefits. However, unless the government and the app makers can convince a significant section of the population to use digital contact apps, desired results cannot be achieved. This study aims to focus on analyzing the perception of citizens belonging to developing countries about digital contact tracing.Design/methodology/approachFor this study, data were collected from Twitter. Tweets containing hashtag and the word “contact tracing” were crawled using Python library Tweepy. Tweets across the top five developing countries (India, Brazil, South Africa, Argentina and Columbia) with high COVID-19 cases were collected for this study. After eliminating tweets of other languages, we selected 50,000 unique English tweets for this study. Using the machine learning algorithm, we have detected the sentiment of all the tweets belonging to each country. Structural topic modeling was performed for the tweets to understand the concerns shared by citizens of the developing countries about digital contact tracing.FindingsThe study was conducted in two parts. Study 1 results show that Indians and Brazilians citizens record more negative sentiments toward “digital contact tracing” than other major developing countries. Surprisingly, the citizens of India and Brazil also records more positive sentiments about contact tracing. This shows the polarized nature of the population of both countries while dealing with digital contact tracing. Overall, only 33.3% of total tweets were positively related to contact tracing, while 53.7% of the total tweets were neutral. Study 2 results show that factors such as the reliability of the contact tracing apps, contact tracing may lead to unnecessary panic, invasion of privacy and data misuse as the prominent reasons why the citizens of the five countries feel pessimistic about contact tracing.Originality/valueAfter the COVID-19 strikes, numerous studies were conducted to analyze and suggest the best possible way of implementing digital contact tracing to curb COVID. However, only a handful of studies were conducted examining how the general public perceives the concept of digital contact tracing, especially pertaining to developing countries. This study fills that gap.
目的尽管数字接触者追踪有许多积极的方面,但接触者追踪的隐含性质仍然被怀疑。那些支持追踪接触者的人往往忽视了它所涉及的各种风险,而那些反对追踪接触者的人往往忽视了它的积极好处。然而,除非政府和应用程序开发商能够说服相当一部分人使用数字联系应用程序,否则无法实现预期的结果。本研究旨在分析发展中国家公民对数字接触追踪的看法。设计/方法/方法对于这项研究,数据是从Twitter上收集的。包含标签和“联系人追踪”一词的推文使用Python库Tweepy进行抓取。本研究收集了COVID-19高病例的前五个发展中国家(印度、巴西、南非、阿根廷和哥伦比亚)的推文。在剔除其他语言的推文后,我们选取了5万条唯一的英文推文进行研究。使用机器学习算法,我们检测了属于每个国家的所有推文的情绪。对推文进行了结构主题建模,以了解发展中国家公民对数字接触追踪的共同关注。这项研究分为两部分。研究1的结果显示,与其他主要发展中国家相比,印度和巴西公民对“数字接触追踪”的负面情绪更多。令人惊讶的是,印度和巴西的公民也对追踪接触者表现出更积极的态度。这表明在处理数字接触者追踪时,两国人口的两极化性质。总体而言,只有33.3%的推文与接触者追踪呈正相关,而53.7%的推文是中性的。研究2结果显示,接触者追踪应用的可靠性、接触者追踪可能导致不必要的恐慌、侵犯隐私和数据滥用等因素是五国公民对接触者追踪持悲观态度的主要原因。在COVID-19袭击之后,进行了大量研究,以分析和建议实施数字接触者追踪以遏制COVID-19的最佳方法。然而,只有少数研究调查了公众如何看待数字接触者追踪的概念,特别是在发展中国家。这项研究填补了这一空白。
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引用次数: 10
Challenges in successful implementation of Digital contact tracing to curb COVID-19 from global citizen's perspective: a text analysis study 从全球公民的角度成功实施数字接触者追踪以遏制COVID-19的挑战:一项文本分析研究
Pub Date : 2020-10-28 DOI: 10.1108/ijpcc-09-2020-0147
S. Praveen, Rajesh Ittamalla, Dhilip Subramanian
PurposeThe word “digital contact tracing” is often met with different reactions: the reaction that passionately supports it, the reaction that neither supports nor oppose and the one that vehemently opposes it. Those who support the notion of digital contact tracing vouch for its effectiveness and how the complicated process can be made simpler by implementing digital contact tracing, and those who oppose it often criticize the imminent threats it possesses. However, without earning the support of a large population, it would be difficult for any government to implement digital contact tracing to perfection. The purpose of this paper is to analyze, using machine learning, how different continents have different sentiments over digital contact tracing being used as a measure to curb COVID-19.Design/methodology/approachFor the analysis, data were collected from Twitter. Tweets that contain the hashtag and the word “digital contact tracing” were crawled using Python library Tweepy. Tweets across countries of four continents were collected from March 2020 to August 2020. In total, 70,212 tweets were used for this study. Using the machine learning algorithm, the authors detected the sentiment of all the tweets belonging to each continent. Structural topic modeling was used to understand the overall significant issues people voice out by global citizens while sharing their opinions on digital contact tracing.FindingsThis study was conducted in two parts. Study one results show that North American and European citizens share more negative sentiments toward “digital contact tracing.” The citizens of the Asian and South American continent mostly share neutral sentiments regarding the digital contact tracing. Overall, only 33% of total tweets were positively related to contact tracing, whereas 52% of the total tweets were neutral. Study two results show that factors such as fear of government using contact tracing to spy on its people, the feeling of being unsafe and contact tracing being used to promote an agenda were the three major issues concerning the overall general public.Originality/valueDespite numerous studies being conducted about how to implement the contact tracing efficiently, minimal studies were done to explore the possibility and challenges in implementing it. This study fills the gap.
目的“数字接触追踪”一词经常会遇到不同的反应:热烈支持的反应,既不支持也不反对的反应,以及强烈反对的反应。那些支持数字接触者追踪概念的人保证其有效性,以及如何通过实施数字接触者追踪来简化复杂的过程,而那些反对它的人经常批评它所具有的迫在眉睫的威胁。然而,如果没有得到广大民众的支持,任何政府都很难完美地实施数字接触追踪。本文的目的是利用机器学习分析不同大陆对使用数字接触者追踪作为遏制COVID-19措施的不同看法。设计/方法/方法对于分析,数据是从Twitter上收集的。包含标签和“数字接触追踪”一词的推文使用Python库Tweepy进行抓取。从2020年3月到2020年8月,收集了四大洲国家的推文。这项研究总共使用了70,212条推文。使用机器学习算法,作者检测了属于每个大洲的所有推文的情绪。结构主题模型用于理解全球公民在分享他们对数字接触追踪的意见时所提出的总体重大问题。本研究分为两部分进行。一项研究结果显示,北美和欧洲公民对“数字接触追踪”持更多负面看法。亚洲和南美大陆的公民对数字追踪接触者的态度大多持中立态度。总的来说,只有33%的推文与接触者追踪呈正相关,而52%的推文是中立的。研究二的结果表明,担心政府使用接触者追踪来监视其人民,不安全的感觉以及接触者追踪被用来推动议程等因素是与整体公众有关的三大问题。独创性/价值尽管关于如何有效地实施接触追踪进行了大量研究,但探索实施接触追踪的可能性和挑战的研究却很少。这项研究填补了这一空白。
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引用次数: 10
Mobile application based speech and voice analysis for COVID-19 detection using computational audit techniques 基于移动应用程序的语音和语音分析,使用计算审计技术进行COVID-19检测
Pub Date : 2020-10-19 DOI: 10.1108/ijpcc-09-2020-0150
Udhaya Sankar S.M., Ganesan R., Jeevaa Katiravan, R. M, Ruhin Kouser R.
PurposeIt has been six months from the time the first case was registered, and nations are still working on counter steering regulations. The proposed model in the paper encompasses a novel methodology to equip systems with artificial intelligence and computational audition techniques over voice recognition for detecting the symptoms. Regular and irregular speech/voice patterns are recognized using in-built tools and devices on a hand-held device. Phenomenal patterns can be contextually varied among normal and presence of asymptotic symptoms.Design/methodology/approachThe lives of patients and healthy beings are seriously affected with various precautionary measures and social distancing. The spread of virus infection is mitigated with necessary actions by governments and nations. Resulting in increased death ratio, the novel coronavirus is certainly a serious pandemic which spreads with unhygienic practices and contact with air-borne droplets of infected patients. With minimal measures to detect the symptoms from the early onset and the rise of asymptotic outcomes, coronavirus becomes even difficult for detection and diagnosis.FindingsA number of significant parameters are considered for the analysis, and they are dry cough, wet cough, sneezing, speech under a blocked nose or cold, sleeplessness, pain in chests, eating behaviours and other potential cases of the disease. Risk- and symptom-based measurements are imposed to deliver a symptom subsiding diagnosis plan. Monitoring and tracking down the symptoms inflicted areas, social distancing and its outcomes, treatments, planning and delivery of healthy food intake, immunity improvement measures are other areas of potential guidelines to mitigate the disease.Originality/valueThis paper also lists the challenges in actual scenarios for a solution to work satisfactorily. Emphasizing on the early detection of symptoms, this work highlights the importance of such a mechanism in the absence of medication or vaccine and demand for large-scale screening. A mobile and ubiquitous application is definitely a useful measure of alerting the officials to take necessary actions by eliminating the expensive modes of tests and medical investigations.
从第一例案例登记到现在已经过去了6个月,各国仍在制定反驾驶法规。本文提出的模型包括一种新的方法,使系统具备人工智能和计算试听技术,而不是语音识别,以检测症状。使用手持设备上的内置工具和设备识别规则和不规则的语音/语音模式。现象模式可以在正常和无症状的情况下有所不同。设计/方法/方法各种预防措施和保持社会距离严重影响病人和健康人的生命。政府和国家采取必要行动,减轻病毒感染的传播。新型冠状病毒是一种严重的大流行,它通过不卫生的做法和接触感染者的空气飞沫传播,导致死亡率上升。由于从早期发病开始检测症状的措施很少,而且无症状结果的增加,冠状病毒的检测和诊断变得更加困难。在分析中考虑了一些重要的参数,它们是干咳、湿咳、打喷嚏、鼻塞或感冒、失眠、胸痛、饮食行为和其他潜在的疾病病例。采用基于风险和症状的测量来提供症状消退诊断计划。监测和追踪造成症状的地区、保持社交距离及其结果、治疗、规划和提供健康食物摄入、提高免疫力措施是减轻疾病的潜在指导方针的其他领域。原创性/价值本文还列出了解决方案在实际场景中令人满意地工作的挑战。这项工作强调早期发现症状,强调了这种机制在缺乏药物或疫苗和大规模筛查需求的情况下的重要性。移动和无处不在的应用程序绝对是一个有用的措施,提醒官员采取必要的行动,消除昂贵的测试和医疗调查模式。
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引用次数: 19
Performance analysis of optimal cluster selection and intrusion detection by hierarchical K-means clustering with hybrid ABC-DT 混合ABC-DT分层k均值聚类的最优聚类选择和入侵检测性能分析
Pub Date : 2020-10-06 DOI: 10.1108/IJPCC-05-2020-0037
Josemila Baby Jesuretnam, Jeba James Rose
PurposeThis paper aims to propose a multi-dimensional hierarchical K-means clustering algorithm for the purpose of intrusion detection. Initially, the clustering set of rules is proposed to shape some of clusters in the network and then the most beneficial clusters are decided on by the use of Cuckoo search optimization set of rules. Finally, an Artificial Bee Colony primarily based selection tree (ABC-DT) classifier is rented to classify the regular and unusual instances present in the network with the aid of the extracted features.Design/methodology/approachIntrusion detection system (IDS) is crucial for the network system; the intruder can take sensitive details about the network. IDS are said to be more effective when it has both high intrusion detection rate and low false alarm rate. Numerous strategies including gadget mastering, records mining and statistical techniques were tested for IDS mission. Recent study reveals that combining multiple classifiers, i.e. classifiers ensemble, can also own better performance than unmarried classifier. In this paper, a comparative study is conducted of the overall performance of four classifiers, i.e. hybrid ABC-DT particle swarm optimization-based K-means clustering (PSO-KM), help vector device (SVM) and K-Nearest neighbour (KNN). All the four classifiers are tested with exceptional packet sizes 1470, 1024, 512 and 256. The experiment is carried out for the speed ranging from turned into done for the velocity ranging from 250Mbps, 500Mbps, 750Mbps, 1.0Gpbs, 1.5Gbps, and 2.0Gbps in terms of accuracy, detection charge, specificity, false alarm charge and computational time. The experimental results reveals that the hybridization of classifiers performs better than the base classifiers in all scenarios.FindingsThis study analyses the performance of hybrid ABC-DT classifier and compares the performance against three well-known classifiers such as PSO-KM, SVM and K-NN. The performances of all the four classifiers are tested with Discovery in Data Mining (KDD) CUP 99 dataset with different packet sizes 1470, 1024, 512 and 256. The results show the classifier performance variations with different speed ranges. From the experimental results and analysis, the hybridization of classifiers such as ABC-DT outperforms the base classifiers in all scenarios.Originality/valueThe novel approach in this paper is used to study the hybrid ABC-DT classifier and compare the performance against three well-known classifiers such as PSO-KM, SVM and K-NN. The discussed concept is used within the network to monitor the traffic to and from all the devices connected in that network.
目的提出一种用于入侵检测的多维分层k均值聚类算法。首先,提出聚类规则集来塑造网络中的一些聚类,然后使用布谷鸟搜索优化规则集来确定最有利的聚类。最后,利用基于人工蜂群的选择树(ABC-DT)分类器,利用提取的特征对网络中存在的规则和异常实例进行分类。入侵检测系统(IDS)对网络系统至关重要;入侵者可以获取有关网络的敏感细节。当入侵检测率高、误报率低时,入侵检测的效率更高。IDS任务测试了许多策略,包括工具掌握、记录挖掘和统计技术。最近的研究表明,组合多个分类器,即分类器集成,也比单一分类器具有更好的性能。本文对基于ABC-DT混合粒子群优化的k -均值聚类(PSO-KM)、帮助向量设备(SVM)和k -近邻(KNN)四种分类器的总体性能进行了比较研究。所有四种分类器都用异常数据包大小1470、1024、512和256进行了测试。从准确率、检测费用、专一性、虚警费用和计算时间等方面,在250Mbps、500Mbps、750Mbps、1.0Gpbs、1.5Gbps和2.0Gbps的速度范围内,对从转弯到完成的速度进行了实验。实验结果表明,混合分类器在所有场景下的性能都优于基本分类器。本研究分析了ABC-DT混合分类器的性能,并与PSO-KM、SVM和K-NN三种知名分类器进行了性能比较。在数据挖掘中的发现(KDD) CUP 99数据集上测试了这四种分类器的性能,数据集的数据包大小分别为1470、1024、512和256。结果表明,在不同的转速范围内,分类器的性能发生了变化。从实验结果和分析来看,ABC-DT等混合分类器在所有场景下的性能都优于基本分类器。本文采用新颖的方法对ABC-DT混合分类器进行了研究,并与PSO-KM、SVM和K-NN等三种知名分类器进行了性能比较。所讨论的概念在网络中用于监视网络中连接的所有设备之间的流量。
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引用次数: 0
Moving ridge neuronal espionage network simulation for reticulum invasion sensing 面向网络入侵感知的移动脊神经间谍网络仿真
Pub Date : 2020-10-01 DOI: 10.1108/IJPCC-05-2020-0036
G. Sreeram, S. Pradeep, K. S. Rao, B. Raju, Nikhat Parveen
PurposeThe paper aims to precise and fast categorization on to transaction evolves into indispensible. The effective capacity difficulty of all the IDS simulates today at below discovery amount of fewer regular barrage associations and therefore the next warning rate.Design/methodology/approachThe reticulum perception is that the methods which examine and determine the scheme of contact on unearths toward number of dangerous and perchance fateful interchanges occurring toward the system. Within character of guaran-teeing the slumberous, opening and uprightness count of to socialize for professional. The precise and fast categorization on to transaction evolves into indispensible. The effective capacity difficulty of all the intrusion detection simulation (IDS) simulates today at below discovery amount of fewer regular barrage associations and therefore the next warning rate. The container with systems of connections are reproduction everything beacon subject to the series of actions to achieve results accepts exists a contemporary well-known method. At the indicated motivation a hybrid methodology supported pairing distinct ripple transformation and human intelligence artificial neural network (ANN) for IDS is projected. The lack of balance of the situation traversing the space beyond information range was eliminated through synthetic minority oversampling technique-based oversampling have low regular object and irregular below examine of the dominant object. We are binding with three layer ANN is being used for classification, and thus the experimental results on knowledge discovery databases are being used for the facts in occurrence of accuracy rate and disclosure estimation toward identical period. True and false made up accepted.FindingsAt the indicated motivation a hybrid methodology supported pairing distinct ripple transformation and human intelligence ANN for IDS is projected. The lack of balance of the situation traversing the space beyond information range was eliminated through synthetic minority oversampling technique-based oversampling have low regular object and irregular below examine of the dominant object.Originality/valueChain interruption discovery is the series of actions for the results knowing the familiarity opening and honor number associate order, the scientific categorization undertaking become necessary. The capacity issues of invasion discovery is the order to determine and examine. The arrangement of simulations at the occasion under discovery estimation for low regular aggression associations and above made up feeling sudden panic amount.
目的对交易进行精确、快速的分类。目前,所有入侵检测系统的有效容量难度都低于常规弹幕关联的发现量,因此下次预警率也低于常规弹幕关联的发现量。设计/方法/途径网络感知是检查和确定接触方案的方法揭示了发生在系统上的危险的和可能是决定性的交换的数量。在保证睡眠、开放和正直品格的前提下,为专业人士的社交计数。对交易进行精确、快速的分类已成为不可缺少的功能。目前所有入侵检测仿真(IDS)的有效容量难度都是在较少规则弹幕关联的发现量以下进行模拟,从而达到下一个预警率。具有连接系统的容器是再现一切信标服从于一系列动作而达到结果的一种公认存在的当代知名方法。在指明的动机下,提出了一种支持不同纹波变换和人类智能人工神经网络(ANN)配对的IDS混合方法。通过综合少数派过采样技术,消除了信息范围外穿越空间的情况不均衡的问题。我们结合三层人工神经网络进行分类,从而将知识发现数据库上的实验结果用于同一时间段的事实发生准确率和披露估计。真假捏造,接受。基于上述动机,提出了一种支持不同纹波变换与人工智能人工神经网络相结合的IDS混合方法。通过综合少数派过采样技术,消除了信息范围外穿越空间的情况不均衡的问题。独创性/价值链中断发现是对结果的熟悉度开启和荣誉数关联顺序的一系列动作,进行科学的分类处理成为必要。入侵发现的能力问题是判定和审查的顺序。在低规则攻击关联及以上发现估计的情况下,模拟的安排弥补了感觉突然恐慌量。
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引用次数: 0
General public's attitude toward governments implementing digital contact tracing to curb COVID-19 - a study based on natural language processing 公众对政府实施数字接触者追踪以遏制COVID-19的态度——一项基于自然语言处理的研究
Pub Date : 2020-09-30 DOI: 10.1108/IJPCC-09-2020-0121
Praveen S.V., Rajesh Ittamalla
PurposeGovernments worldwide are taking various measures to prevent the spreading of COVID virus. One such effort is digital contact tracing. However, the aspect of digital contact tracing was met with criticism, as many critics view this as an attempt of the government to control people and a fundamental breach of privacy. Using machine learning techniques, this study aims to deal with understanding the general public’s emotions toward contact tracing and determining whether there is a change in the attitude of the general public toward digital contact tracing in various months of crises. This study also analyzes the significant concerns voiced out by the general public regarding digital contact tracing.Design/methodology/approachFor the analysis, data were collected from Reddit. Reddit posts discussing the digital contact tracing during COVID-19 crises were collected from February 2020 to July 2020. A total of 5,025 original Reddit posts were used for this study. Natural language processing, which is a part of machine learning, was used for this study to understand the sentiments of the general public about contact tracing. Latent Dirichlet allocation was used to understand the significant issues voiced out by the general public while discussing contact tracing.FindingsThis study was conducted in two parts. Study 1 results show that the percentage of general public viewing the aspect of contact tracing positively had not changed throughout the time period of Data frame (March 2020 to July 2020). However, compared to the initial month of the crises, the later months saw a considerable increase in negative sentiments and a decrease in neutral sentiments regarding the digital contact tracing. Study 2 finds out the significant issues public voices out in their negative sentiments are a violation of privacy, fear of safety and lack of trust in government.Originality/valueAlthough numerous studies were conducted on how to implement contact tracing effectively, to the best of the authors’ knowledge, this is the first study conducted with an objective of understanding the general public’s perception of contact tracing.
世界各国政府正在采取各种措施防止新冠病毒的传播。其中一项努力是数字接触追踪。然而,数字接触追踪方面遭到了批评,因为许多批评者认为这是政府控制人民的企图,是对隐私的根本侵犯。利用机器学习技术,本研究旨在了解公众对接触者追踪的情绪,并确定在危机的各个月里,公众对数字接触者追踪的态度是否发生了变化。这项研究还分析了公众对数字接触追踪的重大关注。设计/方法/方法对于分析,数据是从Reddit收集的。讨论COVID-19危机期间数字接触者追踪的Reddit帖子收集于2020年2月至2020年7月。这项研究共使用了5025个Reddit原创帖子。作为机器学习的一部分,自然语言处理被用于这项研究,以了解公众对接触者追踪的看法。潜在狄利克雷分配用于理解公众在讨论接触者追踪时提出的重要问题。本研究分为两部分进行。研究1结果显示,在整个数据框期间(2020年3月至2020年7月),公众对接触者追踪方面持肯定态度的比例没有变化。然而,与危机发生的最初一个月相比,在随后的几个月里,对数字接触者追踪的负面情绪大幅增加,而中性情绪则有所减少。研究2发现,公众在负面情绪中表达出来的重要问题是侵犯隐私、对安全的恐惧和对政府缺乏信任。原创性/价值虽然就如何有效地实施接触者追踪进行了许多研究,但据作者所知,这是第一次以了解公众对接触者追踪的看法为目的进行研究。
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引用次数: 14
Detection and monitoring of the asymptotic COVID-19 patients using IoT devices and sensors 利用物联网设备和传感器检测和监测新冠肺炎无症状患者
Pub Date : 2020-09-23 DOI: 10.1108/IJPCC-08-2020-0107
Rajeesh Kumar N.V., Arun M., Baraneetharan E., Stanly Jaya Prakash J., Kanchana A., Prabu S.
PurposeMany investigations are going on in monitoring, contact tracing, predicting and diagnosing the COVID-19 disease and many virologists are urgently seeking to create a vaccine as early as possible. Even though there is no specific treatment for the pandemic disease, the world is now struggling to control the spread by implementing the lockdown worldwide and giving awareness to the people to wear masks and use sanitizers. The new technologies, including the Internet of things (IoT), are gaining global attention towards the increasing technical support in health-care systems, particularly in predicting, detecting, preventing and monitoring of most of the infectious diseases. Similarly, it also helps in fighting against COVID-19 by monitoring, contract tracing and detecting the COVID-19 pandemic by connection with the IoT-based smart solutions. IoT is the interconnected Web of smart devices, sensors, actuators and data, which are collected in the raw form and transmitted through the internet. The purpose of this paper is to propose the concept to detect and monitor the asymptotic patients using IoT-based sensors.Design/methodology/approachIn recent days, the surge of the COVID-19 contagion has infected all over the world and it has ruined our day-to-day life. The extraordinary eruption of this pandemic virus placed the World Health Organization (WHO) in a hazardous position. The impact of this contagious virus and scarcity among the people has forced the world to get into complete lockdown, as the number of laboratory-confirmed cases is increasing in millions all over the world as per the records of the government.FindingsCOVID-19 patients are either symptomatic or asymptotic. Symptomatic patients have symptoms such as fever, cough and difficulty in breathing. But patients are also asymptotic, which is very difficult to detect and monitor by isolating them.Originality/valueAsymptotic patients are very hazardous because without knowing that they are infected, they might spread the infection to others, also asymptotic patients might be having very serious lung damage. So, earlier prediction and monitoring of asymptotic patients are mandatory to save their life and prevent them from spreading.
在监测、接触者追踪、预测和诊断COVID-19疾病方面正在进行许多调查,许多病毒学家正在紧急寻求尽早研制出疫苗。尽管没有针对这种大流行疾病的具体治疗方法,但世界正在努力通过在全球范围内实施封锁,并让人们意识到戴口罩和使用消毒剂来控制传播。包括物联网(IoT)在内的新技术正在获得全球关注,以增加卫生保健系统的技术支持,特别是在预测、检测、预防和监测大多数传染病方面。同样,它还通过与基于物联网的智能解决方案的连接,通过监测、合同追踪和检测COVID-19大流行,帮助抗击COVID-19。物联网是由智能设备、传感器、执行器和数据组成的互联网络,这些数据以原始形式收集并通过互联网传输。本文的目的是提出使用基于物联网的传感器检测和监测渐近患者的概念。设计/方法/方法最近几天,新冠肺炎疫情在全球蔓延,破坏了我们的日常生活。这种大流行性病毒的突然爆发使世界卫生组织(世卫组织)处于危险的境地。这种传染性病毒的影响和人民的匮乏迫使世界进入完全封锁状态,因为根据政府的记录,世界各地实验室确诊病例的数量正在以数百万计增加。发现covid -19患者有症状或无症状。有症状的病人有发热、咳嗽和呼吸困难等症状。但患者也是无症状的,这很难通过隔离来发现和监测。无症状患者是非常危险的,因为在不知道自己被感染的情况下,他们可能会将感染传播给他人,而且无症状患者可能会有非常严重的肺损伤。因此,早期预测和监测无症状患者是必要的,以挽救他们的生命,防止他们的传播。
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引用次数: 73
Efficient task scheduling on virtual machine in cloud computing environment 云计算环境下虚拟机的高效任务调度
Pub Date : 2020-09-17 DOI: 10.1108/IJPCC-04-2020-0029
M.Aftab Alam, Mahak, R. Haidri, D. Yadav
PurposeCloud users can access services at anytime from anywhere in the world. On average, Google now processes more than 40,000 searches every second, which is approximately 3.5 billion searches per day. The diverse and vast amounts of data are generated with the development of next-generation information technologies such as cryptocurrency, internet of things and big data. To execute such applications, it is needed to design an efficient scheduling algorithm that considers the quality of service parameters like utilization, makespan and response time. Therefore, this paper aims to propose a novel Efficient Static Task Allocation (ESTA) algorithm, which optimizes average utilization.Design/methodology/approachCloud computing provides resources such as virtual machine, network, storage, etc. over the internet. Cloud computing follows the pay-per-use billing model. To achieve efficient task allocation, scheduling algorithm problems should be interacted and tackled through efficient task distribution on the resources. The methodology of ESTA algorithm is based on minimum completion time approach. ESTA intelligently maps the batch of independent tasks (cloudlets) on heterogeneous virtual machines and optimizes their utilization in infrastructure as a service cloud computing.FindingsTo evaluate the performance of ESTA, the simulation study is compared with Min-Min, load balancing strategy with migration cost, Longest job in the fastest resource-shortest job in the fastest resource, sufferage, minimum completion time (MCT), minimum execution time and opportunistic load balancing on account of makespan, utilization and response time.Originality/valueThe simulation result reveals that the ESTA algorithm consistently superior performs under varying of batch independent of cloudlets and the number of virtual machines’ test conditions.
目的:云用户可以在世界任何地方随时访问服务。谷歌现在平均每秒处理4万多个搜索,每天大约有35亿次搜索。随着加密货币、物联网、大数据等下一代信息技术的发展,产生的数据种类繁多、数量庞大。为了执行这样的应用程序,需要设计一种有效的调度算法,该算法考虑服务质量参数,如利用率、完工时间和响应时间。因此,本文旨在提出一种新的高效静态任务分配(ESTA)算法,以优化平均利用率。设计/方法/方法云计算通过互联网提供诸如虚拟机、网络、存储等资源。云计算遵循按使用付费的计费模式。为了实现高效的任务分配,调度算法问题需要通过资源上的高效任务分配进行交互和解决。ESTA算法的方法是基于最小完成时间法。ESTA智能映射异构虚拟机上的批量独立任务(cloudlets),优化其在基础设施即服务云计算中的利用率。为了评估ESTA的性能,仿真研究比较了Min-Min、迁移成本负载均衡策略、最快资源下最长作业、最快资源下最短作业、最小完成时间(MCT)、最小执行时间和基于makespan、利用率和响应时间的机会性负载均衡策略。独创性/价值仿真结果表明,ESTA算法在不依赖于云的不同批处理和虚拟机数量的测试条件下,始终具有优越的性能。
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引用次数: 3
Multi-utility framework: blockchain exchange platform for sustainable development 多用途框架:区块链可持续发展交流平台
Pub Date : 2020-09-17 DOI: 10.1108/IJPCC-06-2020-0059
J. B. Abdo, S. Zeadally
PurposeThe purpose of this paper is to design a sustainable development platform for water and energy peer-to-peer trading that is financially and economically feasible. Water and other resources are becoming scarcer every day, and developing countries are the neediest for an immediate intervention. Water, as a national need, is considered to be one of the most precious commodities, but it is also one of the main causes for conflicts in the 21st century. Rainwater harvesting and peer-to-peer trading of the harvested water is one of the most convenient, scalable and sustainable solutions but faces organization challenges such as the absence of suitable business models motivating normal users to sell their generated resources (such as water and energy), currency and financial settlement complexities and single utility markets.Design/methodology/approachThis paper proposes a multi-utility trading platform based on the blockchain technology which can address the challenges faced by peer-to-peer trading for resources such as energy and water.FindingsThis paper presents a peer-to-peer multi-utility trading platform that solves the shortcomings of existing utility frameworks reported in the current literature.Originality/valueThis proposed platform meets the needs of developing countries as well as rural areas of developed countries. The open nature of the proposed design makes it suitable for adoption and use by various stakeholders.
本文的目的是设计一个可持续发展的水和能源点对点交易平台,在财务和经济上都是可行的。水和其他资源日益稀缺,发展中国家是最需要立即干预的。水,作为一个国家的需要,被认为是最宝贵的商品之一,但它也是21世纪冲突的主要原因之一。雨水收集和收集的水的点对点交易是最方便、可扩展和可持续的解决方案之一,但面临着组织挑战,例如缺乏合适的商业模式来激励普通用户出售他们产生的资源(如水和能源)、货币和金融结算的复杂性以及单一公用事业市场。本文提出了一种基于区块链技术的多用途交易平台,可以解决能源和水等资源的点对点交易所面临的挑战。本文提出了一个点对点多效用交易平台,解决了当前文献中报道的现有效用框架的缺点。这个平台既满足发展中国家的需求,也满足发达国家农村地区的需求。所建议的设计的开放性使其适合各种利益相关者的采用和使用。
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引用次数: 7
期刊
Int. J. Pervasive Comput. Commun.
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