Online

摘要： This study aimed to clarify the changes in nurses’ cognition about the rate and likelihood of implementation of daily ethical nursing items used in pediatric care before and after attending online workshops using the Pediatric Nursing Care Model (PNCM). A 1.5-hour online workshop was held twice over two weeks. A total of nine nurses participated in the program. These online workshops using PNCM helped achieve the original goals and the results revealed a positive outcome of the workshops. We should devise an educational program to arouse participants’ interest and comprehension to make the most of online competency.

摘要： Purpose:This study aimed to examine the usage,acceptability,usability,perceived usefulness,and satisfaction of a web-based video-tailored physical activity(PA)intervention(TaylorActive)in adults.Methods:In 2013-2014,501 Australian adults aged 18+years were randomized into a video-tailored intervention,text-tailored intervention,or control group.Over 3 months,the intervention groups received access to 8 sessions of personally tailored PA advice delivered via the TaylorActive website.Only the delivery method differed between the intervention groups:video-tailored vs.text-tailored.Google Analytics and telephone surveys conducted at post intervention(3 months)were used to assess intervention usage,acceptability,usability,perceived usefulness,and satisfaction.Quantitative and qualitative process data were analyzed using descriptive statistics and thematic content analysis.Results:Of 501 recruited adults,259 completed the 3-month post-intervention survey(52%retention).Overall,usage of the TaylorActive website with respect to number of website visits,intervention sessions,and action plans completed was modest in both the video-tailored(7.6士7.2 visits,mean±SD)and text-tailored(7.3±5.4 visits)groups with no significant between-group differences.The majority of participants in all groups used the TaylorActive website less than once in 2 weeks(66.7%video-tailored,62.7%text-tailored,87.5%control;p<0.001).Acceptability was rated mostly high in all groups and in some instances,significantly higher in the intervention groups compared to the control group(p<0.010).Usability was also rated high;mean Systems Usability Scores were 77.3(video-tailored),75.7(text-tailored),and 74.1(control)with no significant between-group differences.Perceived usefulness of the TaylorActive intervention was low,though mostly rated higher in the intervention groups compared to the control group(p<0.010).Satisfaction with the TaylorActive website was mixed.Participants in both intervention groups liked its ease of use,personalized feedback,and tracking of progress,but also found completing action plans and survey questions for each session repetitive and tedious.Conclusion:Providing personally tailored PA advice on its own(through either video or text)is likely insufficient to ensure good retention,usage,perceived usefulness,and satisfaction with a web-based PA intervention.Strategies to address this may include the incorporation of additional intervention components such as activity trackers,social interactions,gamification,as well as the use of advanced artificial intelligence and machine learning technologies to allow more personalized dialogue with participants.

摘要： In the beginning of 2022,China Cultural Center(CCC)in Paris launched a series of online events to celebrate the Chinese New Year and the 2022 Winter Olympics un der the brand names of"Happy Chinese New Year"and"China Ice&Snow Tourism Overseas Promotion Season".

摘要： The online 10-day 131st Canton Fair was ended on April 24th after having been online for ten days.The on­line platform of this year’s Canton Fair ran smoothly and a total of 536,000 overseas buyers from 228 countries and regions registered to attend the Fair,which reached a record high was up 48%when compared to the 129th ses­sion and up 41.8%compared with the 130th session,said Xu Bing,spokesman of the Canton Fair and deputy director of the China Foreign Trade Center.

摘要： BACKGROUND Nursing officers are an integral component of any medical team.They participate in taking care of basic airway management and assist in advanced airway management,specifically amidst the current coronavirus disease 2019(COVID-19)pandemic.AIM To assess the efficacy of a standardized web-based training module for nurses in preparedness to fight against COVID-19.METHODS The training was held in three sessions of 1 h each,consisting of live audio-visual lectures,case scenarios,and skill demonstrations.The sequence of airway equipment,drug preparation,airway examination,and plans of airway management was demonstrated through mannequin-based video-clips.RESULTS Pre-and post-test scores as well as objective structured clinical examination scores were analyzed using Student’s t-test and the Likert scale was used for feedback assessment.It was found that the mean score out of the total score of 20 was 8.47±4.2 in the pre-test,while in the post-test it was 17.4±1.8(P value<0.001).The participants also felt self-reliant in executing the roles of airway assistant(63.3%)and drug assistant(74.3%).Fear of self-infection with COVID-19 was also high,as 66%of participants feared working with the patient’s airway.CONCLUSION Amidst this COVID-19 emergency,when the health care systems are being persistently challenged,training of nursing staff in the safe conduct of airway management can ensure delivery of life-saving treatment.

摘要： The issue of whether online teaching could replace traditional classroom(TC)teaching has attracted the attention of researchers in the applied linguistics literature.The current study attempted to shed light on this proposition by testing it on the difficult linguistic target of conditional if-clauses in English.The difficulty of these clauses stems from the fact that different tenses are used to express meanings that are sometimes not related to the tense used.The study recruited 49 participants,who were divided into two groups(23 in the online group,26 in the TC teaching group)and given a multiple-choice task containing 20 items.The study adopted a longitudinal research design(pretest and posttest).Each group was pretested before receiving just one two-hour treatment session.Then both groups were posttested.The results showed that both groups struggled with the second and third types of conditionals more than the zero and first types.The TC teaching group improved in the posttest in all types of conditionals.The online group improved in only two types of conditionals(zero and first).The TC teaching group outperformed the online group in the second and third conditionals.The findings indicate that classroom learning is superior to online learning and that,depending on their type,some conditionals in English are more difficult to learn than others.

摘要： In Laos,the series of cultural events 2022"Happy Chinese New Year",in the theme of watching the Winter Olympics and celebrating the New Year,was continuously launched with a strong momentum for more than a month around the Spring Festival,attracting broad attention and warm welcome of the Laos people and the media of China and Laos.Among them,"Happy Chinese New Year"Online Temple Fair really inspired its popularity in Laos.

摘要： Digital communication and people-to-people connectivity features two pillars of external cultural exchanges and tourism promotion,while online and onsite formats are two different tools for such exchanges and promotion.They should focus on the national objective to strengthen international communication capacity and tell China's stories well and the significant mission to build a system of speech and narrative with Chinese characteristics,common value and international recognition.

摘要： On February 4,President of China Institute of International Studies(CIIS)Xu Bu was invited to attend a meeting between Prime Minister of Pakistan Imran Khan and experts from Chinese think tanks.Prime Minister Khan gave a keynote speech on China-Pakistan relations and the situation in South Asia and Afghanistan,and exchanged views with participating Chinese experts.Speaking highly of China's achievements and the all-weather strategic partnership between China and Pakistan,Khan expressed hopes for more exchanges with Chinese think tanks in support of further development in bilateral relations.

摘要： With technological advancement and the COVID pandemic,online speaking assessment is increasingly used in language teaching.Two modes are developed:online synchronous testing(direct human-to-human interview)and online asynchronous testing(semi-direct human-to-machine interview).Ample literature has explored how each of the two online modes differs from traditional face-to-face speaking assessments.However,few studies have investigated the differences between the two modes,especially in terms of examinees’affective preferences.This study,therefore,compares the extent to which each mode is accepted and favored by test takers and explores why such an affective preference emerges.The participants are 46 college students enrolled in an Elementary Chinese course.They completed a survey that investigates their level of motivation,self-confidence,and anxiety in the two types of online speaking tests.An open-ended question item solicited further explanations from test-takers.Results showed a strong affective preference for synchronous assessment,as manifested by a higher level of motivation and self-confidence and a lower level of anxiety.Possible reasons are discussed based on students’written responses.The study is theoretically significant as it identifies factors on student experience and performance in online speaking assessments.It also provides practical guidance for language teachers in optimizing online oral tests.

摘要： Data Stream (Time series database) has been widely used in aspect of Web monitor and sensor net. Mining on data streams has been a brand new research field in recent years, as the representation of data streams turned to be the critical problem of this field. In this paper, we propose a novel segmentation algorithm, which can represented data stream in an effective and compact fashion. We first introduce the general view of Piecewise Linear Representation which represents data streams, typical segment algorithms on data streams and their features. After that, we present some ideas on improving performance and compress efficiency of segmentation algorithm using PLR, and introduce a fast Sliding Window based algorithm on data stream segmentation using linear regression. Detailed experiments have been conducted to evaluate the performance of proposed method, and the results show the superiority of our algorithm.

摘要： Data Stream (Time series database) has been widely used in aspect of Web monitor and sensor net. Mining on data streams has been a brand new research field in recent years, as the representation of data streams turned to be the critical problem of this field. In this paper, we propose a novel segmentation algorithm, which can represented data stream in an effective and compact fashion. We first introduce the general view of Piecewise Linear Representation which represents data streams, typical segment algorithms on data streams and their features. After that, we present some ideas on improving performance and compress efficiency of segmentation algorithm using PLR, and introduce a fast Sliding Window based algorithm on data stream segmentation using linear regression. Detailed experiments have been conducted to evaluate the performance of proposed method, and the results show the superiority of our algorithm.

摘要： Data Stream (Time series database) has been widely used in aspect of Web monitor and sensor net. Mining on data streams has been a brand new research field in recent years, as the representation of data streams turned to be the critical problem of this field. In this paper, we propose a novel segmentation algorithm, which can represented data stream in an effective and compact fashion. We first introduce the general view of Piecewise Linear Representation which represents data streams, typical segment algorithms on data streams and their features. After that, we present some ideas on improving performance and compress efficiency of segmentation algorithm using PLR, and introduce a fast Sliding Window based algorithm on data stream segmentation using linear regression. Detailed experiments have been conducted to evaluate the performance of proposed method, and the results show the superiority of our algorithm.

摘要： Data Stream (Time series database) has been widely used in aspect of Web monitor and sensor net. Mining on data streams has been a brand new research field in recent years, as the representation of data streams turned to be the critical problem of this field. In this paper, we propose a novel segmentation algorithm, which can represented data stream in an effective and compact fashion. We first introduce the general view of Piecewise Linear Representation which represents data streams, typical segment algorithms on data streams and their features. After that, we present some ideas on improving performance and compress efficiency of segmentation algorithm using PLR, and introduce a fast Sliding Window based algorithm on data stream segmentation using linear regression. Detailed experiments have been conducted to evaluate the performance of proposed method, and the results show the superiority of our algorithm.

摘要： Data Stream (Time series database) has been widely used in aspect of Web monitor and sensor net. Mining on data streams has been a brand new research field in recent years, as the representation of data streams turned to be the critical problem of this field. In this paper, we propose a novel segmentation algorithm, which can represented data stream in an effective and compact fashion. We first introduce the general view of Piecewise Linear Representation which represents data streams, typical segment algorithms on data streams and their features. After that, we present some ideas on improving performance and compress efficiency of segmentation algorithm using PLR, and introduce a fast Sliding Window based algorithm on data stream segmentation using linear regression. Detailed experiments have been conducted to evaluate the performance of proposed method, and the results show the superiority of our algorithm.

摘要： Data Stream (Time series database) has been widely used in aspect of Web monitor and sensor net. Mining on data streams has been a brand new research field in recent years, as the representation of data streams turned to be the critical problem of this field. In this paper, we propose a novel segmentation algorithm, which can represented data stream in an effective and compact fashion. We first introduce the general view of Piecewise Linear Representation which represents data streams, typical segment algorithms on data streams and their features. After that, we present some ideas on improving performance and compress efficiency of segmentation algorithm using PLR, and introduce a fast Sliding Window based algorithm on data stream segmentation using linear regression. Detailed experiments have been conducted to evaluate the performance of proposed method, and the results show the superiority of our algorithm.

摘要： 本发明公开的属于测量装置技术领域，具体为一种简单的Online厚密度及质量分布测量装置，包括第一装置外罩、传动装置主机、切刀、第二装置外罩和载物台，所述第一装置外罩的内腔嵌套所述传动装置主机，所述传动装置主机的底部通过螺栓固定连接所述切刀，该种简单的Online厚密度及质量分布测量装置，嵌套气压式传动装置、切割取样与测量一体式系统、附有陀螺仪的称量系统，可快速便捷的测量被测目标的视觉厚度、实际厚度、质量、视觉体积、实际体积、真密度、假密度、挤压强度，快速绘制被测目标的视觉厚度与实际厚度的过程曲线、被测目标在不同厚度变化下的挤压强度曲线，同时能够测量被测目标的质量分布均匀度。

摘要： 本发明提出了一种基于改进Online Boosting和卡尔曼滤波器改进的TLD跟踪方法，属于机器视觉、人工智能、人机交互、目标跟踪技术领域。该方法包括如下步骤：(1)初始化：利用选定目标并仿射变换形成的初始样本集初始化改进Online Boosting分类器和P‑N学习器；(2)图像跟踪：选取特征点，用两次L‑K光流法对其进行跟踪，两次跟踪误差与阈值比较，得出跟踪结果；(3)图像检测：经卡尔曼滤波器、方差分类器、Online Boosting分类器、KNN分类器后得出检测器结果；(4)综合跟踪与检测结果：评估跟踪器与检测器结果的置信度，得出最终采用哪一模块结果；(5)在线学习：P‑N学习器用来修正跟踪器、检测器结果，并丰富样本集。本发明可有效克服遮挡问题并提高原方法的速度，同时有效提高检测器精度和鲁棒性。

摘要： 本发明提供了一种基于Online Boosting的目标轮廓跟踪方法，在目标精细跟踪的问题中使用超像素对含有跟踪目标的图像进行分块，每一个超像素被看做一个点，这降低了计算的复杂度；使用在线学习的方法来分割目标和背景。传统的Online Boosting算法中，训练样本的权重是相同的，不会随时间的变化而变化。但是在目标精细跟踪问题里面，由于运动目标时刻变化，所以对在线的分类器来说距离当前帧时间越久远的图像帧的权重应该越小，为了实现这种权重逐渐衰减的效果，本发明设计了一种样本权重随时间的久远程度而递减的Online Boosting分类器，随着视频帧数的增加，分类器的性能越来越好，从而实现准确的跟踪目标的精细轮廓。

摘要： 本发明公开一种基于Online‑WSVR算法的车辆位置信息预测方法，其步骤为：1)利用车内组合导航系统实时采集车辆的行驶状态信息；2)依据车辆之前一段时间的行驶状态信息，采用Online‑WSVR算法进行建模，且为每个时间点的数据分发权值，使其对建模系数的贡献不同，增大精确度；3)根据当前的行驶状态信息，利用Online‑WSVR的建模函数实时预测车辆下一刻的位置信息：如果当前GPS信号有效，则将预测出的下一刻经度与纬度信息擦除；如果当前GPS信号失效，则利用Online‑WSVR算法预测出车辆下一刻的经度与纬度信息，并将其写入训练集建模，作为之后预测的建模样本。本发明具有原理简单、适用范围广、定位预测精度高、价廉便携和可靠性好等优点。

摘要： 一种基于Online Boosting的粒子滤波跟踪方法，属于目标跟踪或图像处理技术。本发明通过对跟踪环境中具体情形进行分析，对跟踪行人相互遮挡建立遮挡矩阵，构成粒子滤波模型的中的加权因子，以此来对遮挡行人进行有效刻画，同时在改进的粒子滤波模型中，利用了Online Boosting实时更新刻画目标的优点，对跟踪过程中偏离目标进行了有效的抑制，能够有效的避免目标跟踪过程漂移的发生，使得跟踪更加的准确和鲁棒。本发明充分有效利用了行人运动过程的有效信息，在下一时刻行人目标跟踪时，在目标周围区域进行粒子重建，使得模型能很快地收敛，计算速度快，跟踪准确，同时，本方法对噪声具有较强的鲁棒性，算法稳定性较高。

摘要： 本发明公开的属于测量装置技术领域，具体为一种简单的Online厚密度及质量分布测量装置，包括第一装置外罩、传动装置主机、切刀、第二装置外罩和载物台，所述第一装置外罩的内腔嵌套所述传动装置主机，所述传动装置主机的底部通过螺栓固定连接所述切刀，该种简单的Online厚密度及质量分布测量装置，嵌套气压式传动装置、切割取样与测量一体式系统、附有陀螺仪的称量系统，可快速便捷的测量被测目标的视觉厚度、实际厚度、质量、视觉体积、实际体积、真密度、假密度、挤压强度，快速绘制被测目标的视觉厚度与实际厚度的过程曲线、被测目标在不同厚度变化下的挤压强度曲线，同时能够测量被测目标的质量分布均匀度。

摘要： 本发明公开了一种基于ONLINE‑RLSSVM的毕赤酵母发酵过程软测量方法，首先通过对毕赤酵母发酵过程的工艺机理进行分析，选取合适的辅助变量并根据历史罐批数据建立训练样本数据库；然后对样本数据预处理后进行归一化处理，并使用主元分析法对辅助变量进行降维，将这几个主元综合变量作为ONLINE‑RLSSVM的训练样本数据库；接着使用萤火虫‑果蝇混合优化算法在线优化惩罚系数c与宽度系数σ

摘要： 本发明提出了一种基于改进Online Boosting和卡尔曼滤波器改进的TLD跟踪方法，属于机器视觉、人工智能、人机交互、目标跟踪技术领域。该方法包括如下步骤：(1)初始化：利用选定目标并仿射变换形成的初始样本集初始化改进Online Boosting分类器和P‑N学习器；(2)图像跟踪：选取特征点，用两次L‑K光流法对其进行跟踪，两次跟踪误差与阈值比较，得出跟踪结果；(3)图像检测：经卡尔曼滤波器、方差分类器、Online Boosting分类器、KNN分类器后得出检测器结果；(4)综合跟踪与检测结果：评估跟踪器与检测器结果的置信度，得出最终采用哪一模块结果；(5)在线学习：P‑N学习器用来修正跟踪器、检测器结果，并丰富样本集。本发明可有效克服遮挡问题并提高原方法的速度，同时有效提高检测器精度和鲁棒性。

摘要： 一种基于Online Boosting的粒子滤波跟踪方法，属于目标跟踪或图像处理技术。本发明通过对跟踪环境中具体情形进行分析，对跟踪行人相互遮挡建立遮挡矩阵，构成粒子滤波模型的中的加权因子，以此来对遮挡行人进行有效刻画，同时在改进的粒子滤波模型中，利用了Online Boosting实时更新刻画目标的优点，对跟踪过程中偏离目标进行了有效的抑制，能够有效的避免目标跟踪过程漂移的发生，使得跟踪更加的准确和鲁棒。本发明充分有效利用了行人运动过程的有效信息，在下一时刻行人目标跟踪时，在目标周围区域进行粒子重建，使得模型能很快地收敛，计算速度快，跟踪准确，同时，本方法对噪声具有较强的鲁棒性，算法稳定性较高。

摘要： 本发明涉及服务器电路控制技术领域，具体涉及一种控制CPU online和offline的方法。该方法通过使用带EEPROM的IO Expander代替采用跳帽进行控制CPU online和offline切换的方案，既可以实现远程控制，又可以存储当前配置，不用再担心断电造成的配置丢失的情况，避免了使用跳帽的控制方式需要开箱操作而造成的操作复杂、影响散热等不利影响。