简介：InspiredbytheideasofSwarmIntelligenceandthe'globalbrain',aconceptof'communityintelligence'issuggestedinthepresentpaper,reflectingthatsome'intelligent'featuresmayemergeinaWeb-mediatedonlinecommunityfrominteractionsandknowledge-transmissionsbetweenthecommumtymembers.Thispossibleresearchfieldofcommunityintelligenceisthenexaminedunderthebackgroundsof'community'and'intelligence'researches.Furthermore,aconceptualmodelofcommunityintelligenceisdevelopedfromtwoviews.Fromthestructuralview,thecommunityintelligentsystemismodeledasaknowledgesupernetworkthatiscomprisedoftripleinterwovennetworksofthemedianetwork,thehumannetwork,andtheknowledgenetwork.Furthermore,basedonadyadofknowledgeintwoformsof'knowing'and'knoware',thedynamicviewdescribesthebasicmechanicsoftheformationandevolutionof'communityintelligence'.Afewrelevantresearchissuesareshortlydiscussedonthebasisoftheproposedconceptualmodel.

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简介：复杂地球物理的数据的倒置总是解决多参数，非线性、多模式的优化问题。寻找最佳的倒置答案类似于当寻找食物时，在象鸟和蚂蚁那样的群观察的社会行为。在这篇文章，首先，粒子群优化算法详细被描述，并且蚂蚁殖民地算法改善了。然后，方法被用于地球物理的倒置问题的三种不同类型：(1)对噪音敏感的一个线性问题，(2)线性、非线性的问题的同步倒置，并且(3)一个非线性的问题。结果验证他们的可行性和效率。与常规基因算法相比并且退火模仿，他们有更高的集中速度和精确性的优点。与伪相比--牛顿方法和Levenberg-Marquardt方法，他们与克服局部地最佳的答案的能力更好工作。

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简介：Exploringthehumanbrainisperhapsthemostchallengingandfascinatingscientificissueinthe21stcentury.Itwillfacilitatethedevelopmentofvariousaspectsofthesociety,includingeconomics,education,healthcare,nationaldefenseanddailylife.Theartificialintelligencetechniquesarebecomingusefulasanalternatemethodofclassicaltechniquesorasacomponentofanintegratedsystem.Theyareusedtosolvecomplicatedproblemsinvariousfieldsandbecomingincreasinglypopularnowadays.Especially,theinvestigationofhumanbrainwillpromotetheartificialintelligencetechniques,utilizingtheaccumulatingknowledgeofneuroscience,brain-machineinterfacetechniques,algorithmsofspikingneuralnetworksandneuromorphicsupercomputers.Consequently,weprovideacomprehensivesurveyoftheresearchandmotivationsforbrain-inspiredartificialintelligenceanditsengineeringoveritshistory.Thegoalsofthisworkaretoprovideabriefreviewoftheresearchassociatedwithbrain-inspiredartificialintelligenceanditsrelatedengineeringtechniques,andtomotivatefurtherworkbyelucidatingchallengesinthefieldwherenewresearchesarerequired.

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简介：信息和通讯技术和“智力”(ICT)上的概念第一被定义，为ICT的环境和要求上的分析然后被跟随。基于定义和分析，可能为ICT有用的智力途径上的调查因此被做。从调查得出的结论是由说智力途径是为ICT的全部的进一步的开发的钥匙之一应该因此在年里从ICT研究人员收到更多注意来的一个建议。

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简介：ＡｒｔｉｆｉｃｉａｌＩｎｔｅｌｌｉｇｅｎｃｅＥｍｂｅｄｄｅｄＯｂｊｅｃｔ－ＯｒｉｅｎｔｅｄＭｅｔｈｏｄｏｌｏｇｙＦｏｒＭｏｄｅｌＢａｓｅｄＤｅｃｉｓｉｏｎＳｕｐｐｏｒｔ￥ＦｅｎｇＳｈａｎ；ＴｉａｎＹｕａｎ；ＬｉＴｏｎｇ＆ＣａｉＪｕｎ（Ｉｎｓｔｉｔｕｔ...

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简介：AbstractFor the detection of steatosis, quantitative ultrasound imaging techniques have achieved great progress in past years. Magnetic resonance imaging proton density fat fraction is currently the most accurate test to detect hepatic steatosis. Some blood biomarkers correlate with non-alcoholic steatohepatitis, but the accuracy is modest. Regarding liver fibrosis, liver stiffness measurement by transient elastography (TE) has high accuracy and is widely used across the world. Magnetic resonance elastography is marginally better than TE but is limited by its cost and availability. Several blood biomarkers of fibrosis have been used in clinical trials and hold promise for selecting patients for treatment and monitoring treatment response. This article reviews new developments in the non-invasive assessment of non-alcoholic fatty liver disease (NAFLD). Accumulating evidence suggests that various non-invasive tests can be used to diagnose NAFLD, assess its severity, and predict the prognosis. Further studies are needed to determine the role of the tests as monitoring tools. We cannot overemphasize the importance of context in selecting appropriate tests.

简介：Thispaperinvestigatesthemathematicfeaturesofnon-linearmodelsanddiscussestheprocessingwayofnon-linearfactorswhichcontributestothenon-linearityofanonlinearmodel.Onthebasisoftheerrordefinition,thispaperputsforwardanewadjustmentcriterion,SGPE.Last,thispaperinvestigatesthesolutionofanon-linearregressionmodelinthenon-linearmodelspaceandmakesthecomparisonbetweentheestimatedvaluesinnon-linearmodelspaceandthoseinlinearmodelspace.

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简介：AbstractArtificial intelligence (AI) has proven time and time again to be a game-changer innovation in every walk of life, including medicine. Introduced by Dr. Gunn in 1976 to accurately diagnose acute abdominal pain and list potential differentials, AI has since come a long way. In particular, AI has been aiding in radiological diagnoses with good sensitivity and specificity by using machine learning algorithms. With the coronavirus disease 2019 pandemic, AI has proven to be more than just a tool to facilitate healthcare workers in decision making and limiting physician-patient contact during the pandemic. It has guided governments and key policymakers in formulating and implementing laws, such as lockdowns and travel restrictions, to curb the spread of this viral disease. This has been made possible by the use of social media to map severe acute respiratory syndrome coronavirus 2 hotspots, laying the basis of the "smart lockdown" strategy that has been adopted globally. However, these benefits might be accompanied with concerns regarding privacy and unconsented surveillance, necessitating authorities to develop sincere and ethical government–public relations.

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简介：Multipleintelligence（多元智能）理论为英语教学多元化评价及个性化教学提供了理论基础。它要求教学评价应以促进学生的智能发展为目标，采取多元的评价标准及方式．帮助学生正确地认识自己的智力特点，悦纳自己，拥有自信，促进其自我效能感的形成。

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简介：AbstractCurrently, the diagnosis of tuberculosis (TB) is mainly based on the comprehensive consideration of the patient's symptoms and signs, laboratory examinations and chest radiography (CXR). CXR plays a pivotal role to support the early diagnosis of TB, especially when used for TB screening and differential diagnosis. However, high cost of CXR hardware and shortage of certified radiologists poses a major challenge for CXR application in TB screening in resource limited settings. The latest development of artificial intelligence (AI) combined with the accumulation of a large number of medical images provides new opportunities for the establishment of computer-aided detection (CAD) systems in the medical applications, especially in the era of deep learning (DL) technology. Several CAD solutions are now commercially available and there is growing evidence demonstrate their value in imaging diagnosis. Recently, WHO published a rapid communication which stated that CAD may be used as an alternative to human reader interpretation of plain digital CXRs for screening and triage of TB.