The significance and impact of winning an academic award : a study of early career academics
- Ren, Jing, Shi, Yajie, Shatte, Adrian, Kong, Xiangjie, Xia, Feng
- Authors: Ren, Jing , Shi, Yajie , Shatte, Adrian , Kong, Xiangjie , Xia, Feng
- Date: 2022
- Type: Text , Conference paper
- Relation: 22nd ACM/IEEE Joint Conference on Digital Libraries, JCDL 2022, Virtual, online, 20-24 June 2022, Proceedings of the ACM/IEEE Joint Conference on Digital Libraries
- Full Text: false
- Reviewed:
- Description: Academic award plays an important role in an academic's careerparticularly for early career academics. Previous studies have primarilyfocused on the impact of awards conferred to academics whoe made outstanding contributions to a specific research field, such as the Nobel Prize. In contrast, this paper aims to investigatethe effect of awards conferred to academics at an earlier careerstage, who have the potential to make a great impact in the future. We devise a metric named Award Change Factor (ACF), to evaluatethe change of a recipient's academic behavior after winningan academic award. Next, we propose a model to compare awardrecipients with academics who have similar performance beforewinning an academic award. In summary, we analyze the impact ofan award on the recipients' academic impact and their teams fromdifferent perspectives. Experimental results show that most recipientsdo have improvements in both productivity and citations afterwinning an academic award, while there is no significant impacton publication quality. In addition, receipt of an academic awardnot only expands recipients' collaboration network, but also has apositive effect on their team size. © 2022 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.
Graph learning for anomaly analytics : algorithms, applications, and challenges
- Ren, Jing, Xia, Feng, Lee, Ivan, Noori Hoshyar, Azadeh, Aggarwal, Charu
- Authors: Ren, Jing , Xia, Feng , Lee, Ivan , Noori Hoshyar, Azadeh , Aggarwal, Charu
- Date: 2023
- Type: Text , Journal article
- Relation: ACM Transactions on Intelligent Systems and Technology Vol. 14, no. 2 (2023), p.
- Full Text:
- Reviewed:
- Description: Anomaly analytics is a popular and vital task in various research contexts that has been studied for several decades. At the same time, deep learning has shown its capacity in solving many graph-based tasks, like node classification, link prediction, and graph classification. Recently, many studies are extending graph learning models for solving anomaly analytics problems, resulting in beneficial advances in graph-based anomaly analytics techniques. In this survey, we provide a comprehensive overview of graph learning methods for anomaly analytics tasks. We classify them into four categories based on their model architectures, namely graph convolutional network, graph attention network, graph autoencoder, and other graph learning models. The differences between these methods are also compared in a systematic manner. Furthermore, we outline several graph-based anomaly analytics applications across various domains in the real world. Finally, we discuss five potential future research directions in this rapidly growing field. © 2023 Association for Computing Machinery.
- Authors: Ren, Jing , Xia, Feng , Lee, Ivan , Noori Hoshyar, Azadeh , Aggarwal, Charu
- Date: 2023
- Type: Text , Journal article
- Relation: ACM Transactions on Intelligent Systems and Technology Vol. 14, no. 2 (2023), p.
- Full Text:
- Reviewed:
- Description: Anomaly analytics is a popular and vital task in various research contexts that has been studied for several decades. At the same time, deep learning has shown its capacity in solving many graph-based tasks, like node classification, link prediction, and graph classification. Recently, many studies are extending graph learning models for solving anomaly analytics problems, resulting in beneficial advances in graph-based anomaly analytics techniques. In this survey, we provide a comprehensive overview of graph learning methods for anomaly analytics tasks. We classify them into four categories based on their model architectures, namely graph convolutional network, graph attention network, graph autoencoder, and other graph learning models. The differences between these methods are also compared in a systematic manner. Furthermore, we outline several graph-based anomaly analytics applications across various domains in the real world. Finally, we discuss five potential future research directions in this rapidly growing field. © 2023 Association for Computing Machinery.
Validity of job satisfaction survey scale in Chinese
- Luan, Xiu-yun, Zhai, Qing-guo, Yang, Yu-wen, Wang, Zhihong, Zhai, Yu-bo
- Authors: Luan, Xiu-yun , Zhai, Qing-guo , Yang, Yu-wen , Wang, Zhihong , Zhai, Yu-bo
- Date: 2010
- Type: Text , Conference paper
- Relation: Paper presented at 2010 International Conference on Management Science & Engineering p. 1008-1013
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- Reviewed:
- Description: The aim of this study is to examine the factor structure of the scale of Job Satisfaction Survey (JSS), and its divergent and convergent validity in Chinese population. Data were collected with JSS from 1073 urban employees in Liaoning. Four alternative models were tested with confirmatory factor analysis. The first two models are models validated in the US, while the third and fourth models are composed of five commonly used dimensions of job satisfaction taken from JSS. The research found a poor model fit for the first two models, suggesting a possible national difference between China and the US. However, model three and model four displayed a good model fit, suggesting that the five dimensions in JSS (satisfaction with nature of work, with supervision, with co-worker, with promotion, and with pay) are five distinct dimensions. The correlations between these five facet job satisfaction and PA and NA demonstrated convergent and divergent validity of the scales for these five dimensions of job satisfaction.
- Authors: Luan, Xiu-yun , Zhai, Qing-guo , Yang, Yu-wen , Wang, Zhihong , Zhai, Yu-bo
- Date: 2010
- Type: Text , Conference paper
- Relation: Paper presented at 2010 International Conference on Management Science & Engineering p. 1008-1013
- Full Text:
- Reviewed:
- Description: The aim of this study is to examine the factor structure of the scale of Job Satisfaction Survey (JSS), and its divergent and convergent validity in Chinese population. Data were collected with JSS from 1073 urban employees in Liaoning. Four alternative models were tested with confirmatory factor analysis. The first two models are models validated in the US, while the third and fourth models are composed of five commonly used dimensions of job satisfaction taken from JSS. The research found a poor model fit for the first two models, suggesting a possible national difference between China and the US. However, model three and model four displayed a good model fit, suggesting that the five dimensions in JSS (satisfaction with nature of work, with supervision, with co-worker, with promotion, and with pay) are five distinct dimensions. The correlations between these five facet job satisfaction and PA and NA demonstrated convergent and divergent validity of the scales for these five dimensions of job satisfaction.
Managing depression with complementary and alternative medicine therapies: a scientometric analysis and visualization of research activities
- Zhao, Fei-Yi, Xu, Peijie, Zheng, Zhen, Conduit, Russell, Xu, Yan, Yue, Li-Ping, Wang, Hui-Ru, Wang, Yan-Mei, Li, Yuan-Xin, Li, Chun-Yan, Zhang, Wen-Jing, Fu, Qiang-Qiang, Kennedy, Gerard
- Authors: Zhao, Fei-Yi , Xu, Peijie , Zheng, Zhen , Conduit, Russell , Xu, Yan , Yue, Li-Ping , Wang, Hui-Ru , Wang, Yan-Mei , Li, Yuan-Xin , Li, Chun-Yan , Zhang, Wen-Jing , Fu, Qiang-Qiang , Kennedy, Gerard
- Date: 2023
- Type: Text , Journal article
- Relation: Frontiers in Psychiatry Vol. 14, no. (2023), p.
- Full Text:
- Reviewed:
- Description: Background: Complementary and Alternative Medicine (CAM) interventions may prove to be an attractive option for the treatment of depression. The aim of this scientometric analysis is to determine the global scientific output of research regarding managing depression with CAM and identify the hotspots and frontiers within this theme. Methods: Publications regarding the utilization of CAM for treating depression were collected from the Web of Science Core Collection from 1993 to 2022, and analyzed and visualized by Bibliometrix R-package, VOSviewer, and CiteSpace. Results: A total of 1,710 publications were acquired. The number of annual publications showed an overall rapid upward trend, with the figure peaking at 179 in 2021. The USA was the leading research center. Totally 2,323 distinct institutions involving 7,638 scholars contributed to the research theme. However, most of the cooperation was limited to within the same country, institution or research team. The Journal of Alternative and Complementary Medicine was the most productive periodical. The CAM therapies of most interest to researchers were acupuncture and body–mind techniques, such as yoga, meditation and mindfulness. Systematic review and meta-analysis are commonly used methods. “Inflammation,” “rating scale” and “psychological stress” were identified as the most studied trend topics recently. Conclusion: Managing depression with evidence-based CAM treatment is gaining attention globally. Body–mind techniques and acupuncture are growing research hotspots or emerging trending topics. Future studies are predicted to potentially investigate the possible mechanisms of action underlying CAM treatments in reducing depression in terms of modulation of psychological stress and inflammation levels. Cross-countries/institutes/team research collaborations should be encouraged and further enhanced. Copyright © 2023 Zhao, Xu, Zheng, Conduit, Xu, Yue, Wang, Wang, Li, Li, Zhang, Fu and Kennedy.
- Authors: Zhao, Fei-Yi , Xu, Peijie , Zheng, Zhen , Conduit, Russell , Xu, Yan , Yue, Li-Ping , Wang, Hui-Ru , Wang, Yan-Mei , Li, Yuan-Xin , Li, Chun-Yan , Zhang, Wen-Jing , Fu, Qiang-Qiang , Kennedy, Gerard
- Date: 2023
- Type: Text , Journal article
- Relation: Frontiers in Psychiatry Vol. 14, no. (2023), p.
- Full Text:
- Reviewed:
- Description: Background: Complementary and Alternative Medicine (CAM) interventions may prove to be an attractive option for the treatment of depression. The aim of this scientometric analysis is to determine the global scientific output of research regarding managing depression with CAM and identify the hotspots and frontiers within this theme. Methods: Publications regarding the utilization of CAM for treating depression were collected from the Web of Science Core Collection from 1993 to 2022, and analyzed and visualized by Bibliometrix R-package, VOSviewer, and CiteSpace. Results: A total of 1,710 publications were acquired. The number of annual publications showed an overall rapid upward trend, with the figure peaking at 179 in 2021. The USA was the leading research center. Totally 2,323 distinct institutions involving 7,638 scholars contributed to the research theme. However, most of the cooperation was limited to within the same country, institution or research team. The Journal of Alternative and Complementary Medicine was the most productive periodical. The CAM therapies of most interest to researchers were acupuncture and body–mind techniques, such as yoga, meditation and mindfulness. Systematic review and meta-analysis are commonly used methods. “Inflammation,” “rating scale” and “psychological stress” were identified as the most studied trend topics recently. Conclusion: Managing depression with evidence-based CAM treatment is gaining attention globally. Body–mind techniques and acupuncture are growing research hotspots or emerging trending topics. Future studies are predicted to potentially investigate the possible mechanisms of action underlying CAM treatments in reducing depression in terms of modulation of psychological stress and inflammation levels. Cross-countries/institutes/team research collaborations should be encouraged and further enhanced. Copyright © 2023 Zhao, Xu, Zheng, Conduit, Xu, Yue, Wang, Wang, Li, Li, Zhang, Fu and Kennedy.
A quantitative risk assessment model involving frequency and threat degree under line-of-business services for infrastructure of emerging sensor networks
- Jing, Xu, Hu, Hanwen, Yang, Huijun, Au, Man, Li, Shuqin, Xiong, Naixue, Imran, Muhammad, Vasilakos, Athanasios
- Authors: Jing, Xu , Hu, Hanwen , Yang, Huijun , Au, Man , Li, Shuqin , Xiong, Naixue , Imran, Muhammad , Vasilakos, Athanasios
- Date: 2017
- Type: Text , Journal article
- Relation: Sensors (Switzerland) Vol. 17, no. 3 (2017), p.
- Full Text:
- Reviewed:
- Description: The prospect of Line-of-Business Services (LoBSs) for infrastructure of Emerging Sensor Networks (ESNs) is exciting. Access control remains a top challenge in this scenario as the service provider’s server contains a lot of valuable resources. LoBSs’ users are very diverse as they may come from a wide range of locations with vastly different characteristics. Cost of joining could be low and in many cases, intruders are eligible users conducting malicious actions. As a result, user access should be adjusted dynamically. Assessing LoBSs’ risk dynamically based on both frequency and threat degree of malicious operations is therefore necessary. In this paper, we proposed a Quantitative Risk Assessment Model (QRAM) involving frequency and threat degree based on value at risk. To quantify the threat degree as an elementary intrusion effort, we amend the influence coefficient of risk indexes in the network security situation assessment model. To quantify threat frequency as intrusion trace effort, we make use of multiple behavior information fusion. Under the influence of intrusion trace, we adapt the historical simulation method of value at risk to dynamically access LoBSs’ risk. Simulation based on existing data is used to select appropriate parameters for QRAM. Our simulation results show that the duration influence on elementary intrusion effort is reasonable when the normalized parameter is 1000. Likewise, the time window of intrusion trace and the weight between objective risk and subjective risk can be set to 10 s and 0.5, respectively. While our focus is to develop QRAM for assessing the risk of LoBSs for infrastructure of ESNs dynamically involving frequency and threat degree, we believe it is also appropriate for other scenarios in cloud computing. © 2017 by the authors. Licensee MDPI, Basel, Switzerland.
- Authors: Jing, Xu , Hu, Hanwen , Yang, Huijun , Au, Man , Li, Shuqin , Xiong, Naixue , Imran, Muhammad , Vasilakos, Athanasios
- Date: 2017
- Type: Text , Journal article
- Relation: Sensors (Switzerland) Vol. 17, no. 3 (2017), p.
- Full Text:
- Reviewed:
- Description: The prospect of Line-of-Business Services (LoBSs) for infrastructure of Emerging Sensor Networks (ESNs) is exciting. Access control remains a top challenge in this scenario as the service provider’s server contains a lot of valuable resources. LoBSs’ users are very diverse as they may come from a wide range of locations with vastly different characteristics. Cost of joining could be low and in many cases, intruders are eligible users conducting malicious actions. As a result, user access should be adjusted dynamically. Assessing LoBSs’ risk dynamically based on both frequency and threat degree of malicious operations is therefore necessary. In this paper, we proposed a Quantitative Risk Assessment Model (QRAM) involving frequency and threat degree based on value at risk. To quantify the threat degree as an elementary intrusion effort, we amend the influence coefficient of risk indexes in the network security situation assessment model. To quantify threat frequency as intrusion trace effort, we make use of multiple behavior information fusion. Under the influence of intrusion trace, we adapt the historical simulation method of value at risk to dynamically access LoBSs’ risk. Simulation based on existing data is used to select appropriate parameters for QRAM. Our simulation results show that the duration influence on elementary intrusion effort is reasonable when the normalized parameter is 1000. Likewise, the time window of intrusion trace and the weight between objective risk and subjective risk can be set to 10 s and 0.5, respectively. While our focus is to develop QRAM for assessing the risk of LoBSs for infrastructure of ESNs dynamically involving frequency and threat degree, we believe it is also appropriate for other scenarios in cloud computing. © 2017 by the authors. Licensee MDPI, Basel, Switzerland.
MODEL : motif-based deep feature learning for link prediction
- Wang, Lei, Ren, Jing, Xu, Bo, Li, Jianxin, Luo, Wei, Xia, Feng
- Authors: Wang, Lei , Ren, Jing , Xu, Bo , Li, Jianxin , Luo, Wei , Xia, Feng
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Transactions on Computational Social Systems Vol. 7, no. 2 (2020), p. 503-516
- Full Text:
- Reviewed:
- Description: Link prediction plays an important role in network analysis and applications. Recently, approaches for link prediction have evolved from traditional similarity-based algorithms into embedding-based algorithms. However, most existing approaches fail to exploit the fact that real-world networks are different from random networks. In particular, real-world networks are known to contain motifs, natural network building blocks reflecting the underlying network-generating processes. In this article, we propose a novel embedding algorithm that incorporates network motifs to capture higher order structures in the network. To evaluate its effectiveness for link prediction, experiments were conducted on three types of networks: social networks, biological networks, and academic networks. The results demonstrate that our algorithm outperforms both the traditional similarity-based algorithms (by 20%) and the state-of-the-art embedding-based algorithms (by 19%). © 2014 IEEE.
- Authors: Wang, Lei , Ren, Jing , Xu, Bo , Li, Jianxin , Luo, Wei , Xia, Feng
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Transactions on Computational Social Systems Vol. 7, no. 2 (2020), p. 503-516
- Full Text:
- Reviewed:
- Description: Link prediction plays an important role in network analysis and applications. Recently, approaches for link prediction have evolved from traditional similarity-based algorithms into embedding-based algorithms. However, most existing approaches fail to exploit the fact that real-world networks are different from random networks. In particular, real-world networks are known to contain motifs, natural network building blocks reflecting the underlying network-generating processes. In this article, we propose a novel embedding algorithm that incorporates network motifs to capture higher order structures in the network. To evaluate its effectiveness for link prediction, experiments were conducted on three types of networks: social networks, biological networks, and academic networks. The results demonstrate that our algorithm outperforms both the traditional similarity-based algorithms (by 20%) and the state-of-the-art embedding-based algorithms (by 19%). © 2014 IEEE.
Wearable obstacle avoidance electronic travel aids for blind and visually impaired individuals : a systematic review
- Xu, Peijie, Kennedy, Gerard, Zhao, Fei-Yi, Zhang, Wen-Jing, Van Schyndel, Ron
- Authors: Xu, Peijie , Kennedy, Gerard , Zhao, Fei-Yi , Zhang, Wen-Jing , Van Schyndel, Ron
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 66587-66613
- Full Text:
- Reviewed:
- Description: Background Wearable obstacle avoidance electronic travel aids (ETAs) have been developed to assist the safe displacement of blind and visually impaired individuals (BVIs) in indoor/outdoor spaces. This systematic review aimed to understand the strengths and weaknesses of existing ETAs in terms of hardware functionality, cost, and user experience. These elements may influence the usability of the ETAs and are valuable in guiding the development of superior ETAs in the future. Methods Formally published studies designing and developing the wearable obstacle avoidance ETAs were searched for from six databases from their inception to April 2023. The PRISMA 2020 and APISSER guidelines were followed. Results Eighty-nine studies were included for analysis, 41 of which were judged to be of moderate to high quality. Most wearable obstacle avoidance ETAs mainly depend on camera- and ultrasonic-based techniques to achieve perception of the environment. Acoustic feedback was the most common human-computer feedback form used by the ETAs. According to user experience, the efficacy and safety of the device was usually their primary concern. Conclusions Although many conceptualised ETAs have been designed to facilitate BVIs' independent navigation, most of these devices suffer from shortcomings. This is due to the nature and limitations of the various processors, environment detection techniques and human-computer feedback those ETAs are equipped with. Integrating multiple techniques and hardware into one ETA is a way to improve performance, but there is still a need to address the discomfort of wearing the device and the high-cost. Developing an applicable systematic review guideline along with a credible quality assessment tool for these types of studies is also required. © 2013 IEEE.
- Authors: Xu, Peijie , Kennedy, Gerard , Zhao, Fei-Yi , Zhang, Wen-Jing , Van Schyndel, Ron
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 66587-66613
- Full Text:
- Reviewed:
- Description: Background Wearable obstacle avoidance electronic travel aids (ETAs) have been developed to assist the safe displacement of blind and visually impaired individuals (BVIs) in indoor/outdoor spaces. This systematic review aimed to understand the strengths and weaknesses of existing ETAs in terms of hardware functionality, cost, and user experience. These elements may influence the usability of the ETAs and are valuable in guiding the development of superior ETAs in the future. Methods Formally published studies designing and developing the wearable obstacle avoidance ETAs were searched for from six databases from their inception to April 2023. The PRISMA 2020 and APISSER guidelines were followed. Results Eighty-nine studies were included for analysis, 41 of which were judged to be of moderate to high quality. Most wearable obstacle avoidance ETAs mainly depend on camera- and ultrasonic-based techniques to achieve perception of the environment. Acoustic feedback was the most common human-computer feedback form used by the ETAs. According to user experience, the efficacy and safety of the device was usually their primary concern. Conclusions Although many conceptualised ETAs have been designed to facilitate BVIs' independent navigation, most of these devices suffer from shortcomings. This is due to the nature and limitations of the various processors, environment detection techniques and human-computer feedback those ETAs are equipped with. Integrating multiple techniques and hardware into one ETA is a way to improve performance, but there is still a need to address the discomfort of wearing the device and the high-cost. Developing an applicable systematic review guideline along with a credible quality assessment tool for these types of studies is also required. © 2013 IEEE.
Acupuncture as an independent or adjuvant management to standard care for perimenopausal depression : a systematic review and meta-analysis
- Zhao, Fei, Fu, Qiang-Qiang, Kennedy, Gerard, Conduit, Russell, Zhang, Wen-Jing, Zheng, Zhen
- Authors: Zhao, Fei , Fu, Qiang-Qiang , Kennedy, Gerard , Conduit, Russell , Zhang, Wen-Jing , Zheng, Zhen
- Date: 2021
- Type: Text , Journal article , Review
- Relation: Frontiers in Psychiatry Vol. 12, no. (2021), p.
- Full Text:
- Reviewed:
- Description: Background: Many women with perimenopausal depression (PMD) have sought alternative therapies such as acupuncture because of concerns about risks associated with antidepressant and hormone replacement therapy (HRT). This systematic review aimed to clarify if acupuncture is effective for PMD compared with waitlist control or placebo/sham acupuncture, and if acupuncture alone or combined with standard care (antidepressant and/or HRT) is more effective in ameliorating PMD in comparison with standard care alone. Methods: Randomized controlled trials (RCTs) of PMD treatment via acupuncture vs. waitlist control or placebo/sham acupuncture, and RCTs of PMD treatment via acupuncture alone or combined with Western pharmacotherapy vs. Western pharmacotherapy were searched for from seven databases from inception to December 2020. Cochrane criteria were followed. Results: Twenty-five studies involving 2,213 women were analyzed. Meta-analyses indicated that acupuncture significantly reduced the global scores of Hamilton Depression Scale (HAMD) [standardized mean difference (SMD) = −0.54, 95% CI (−0.91, −0.16), p < 0.01], compared with standard care. The therapeutic effect of acupuncture maintained at 2-, 4-, and 12-week follow-ups. Acupuncture combined with standard care was more effective than standard care alone in decreasing HAMD scores [SMD = −0.82, 95% CI (−1.07, −0.58), p < 0.01]. Too few RCTs were available to assess the clinical efficacy differences between acupuncture and placebo/sham acupuncture or HRT alone. Acupuncture also showed better effects in decreasing Kupperman index (KI) scores, whether compared with antidepressant alone [MD = −4.55, 95% CI (−8.46, −0.65), p = 0.02] or antidepressant combined with HRT [MD = −0.89, 95% CI (−1.34, −0.43), p < 0.01]. Conclusions: In comparison with standard care, acupuncture alone or combined with standard care was associated with significant improvements in PMD and reductions of other menopausal symptoms. This finding suggests that acupuncture may be a useful addition to treatment for PMD. © Copyright © 2021 Zhao, Fu, Kennedy, Conduit, Zhang and Zheng.
- Authors: Zhao, Fei , Fu, Qiang-Qiang , Kennedy, Gerard , Conduit, Russell , Zhang, Wen-Jing , Zheng, Zhen
- Date: 2021
- Type: Text , Journal article , Review
- Relation: Frontiers in Psychiatry Vol. 12, no. (2021), p.
- Full Text:
- Reviewed:
- Description: Background: Many women with perimenopausal depression (PMD) have sought alternative therapies such as acupuncture because of concerns about risks associated with antidepressant and hormone replacement therapy (HRT). This systematic review aimed to clarify if acupuncture is effective for PMD compared with waitlist control or placebo/sham acupuncture, and if acupuncture alone or combined with standard care (antidepressant and/or HRT) is more effective in ameliorating PMD in comparison with standard care alone. Methods: Randomized controlled trials (RCTs) of PMD treatment via acupuncture vs. waitlist control or placebo/sham acupuncture, and RCTs of PMD treatment via acupuncture alone or combined with Western pharmacotherapy vs. Western pharmacotherapy were searched for from seven databases from inception to December 2020. Cochrane criteria were followed. Results: Twenty-five studies involving 2,213 women were analyzed. Meta-analyses indicated that acupuncture significantly reduced the global scores of Hamilton Depression Scale (HAMD) [standardized mean difference (SMD) = −0.54, 95% CI (−0.91, −0.16), p < 0.01], compared with standard care. The therapeutic effect of acupuncture maintained at 2-, 4-, and 12-week follow-ups. Acupuncture combined with standard care was more effective than standard care alone in decreasing HAMD scores [SMD = −0.82, 95% CI (−1.07, −0.58), p < 0.01]. Too few RCTs were available to assess the clinical efficacy differences between acupuncture and placebo/sham acupuncture or HRT alone. Acupuncture also showed better effects in decreasing Kupperman index (KI) scores, whether compared with antidepressant alone [MD = −4.55, 95% CI (−8.46, −0.65), p = 0.02] or antidepressant combined with HRT [MD = −0.89, 95% CI (−1.34, −0.43), p < 0.01]. Conclusions: In comparison with standard care, acupuncture alone or combined with standard care was associated with significant improvements in PMD and reductions of other menopausal symptoms. This finding suggests that acupuncture may be a useful addition to treatment for PMD. © Copyright © 2021 Zhao, Fu, Kennedy, Conduit, Zhang and Zheng.
Graph augmentation learning
- Yu, Shuo, Huang, Huafei, Dao, Minh, Xia, Feng
- Authors: Yu, Shuo , Huang, Huafei , Dao, Minh , Xia, Feng
- Date: 2022
- Type: Text , Conference paper
- Relation: 31st ACM Web Conference, WWW 2022, Virtual, online, 25 April 2022, WWW 2022 - Companion Proceedings of the Web Conference 2022 p. 1063-1072
- Full Text:
- Reviewed:
- Description: Graph Augmentation Learning (GAL) provides outstanding solutions for graph learning in handling incomplete data, noise data, etc. Numerous GAL methods have been proposed for graph-based applications such as social network analysis and traffic flow forecasting. However, the underlying reasons for the effectiveness of these GAL methods are still unclear. As a consequence, how to choose optimal graph augmentation strategy for a certain application scenario is still in black box. There is a lack of systematic, comprehensive, and experimentally validated guideline of GAL for scholars. Therefore, in this survey, we in-depth review GAL techniques from macro (graph), meso (subgraph), and micro (node/edge) levels. We further detailedly illustrate how GAL enhance the data quality and the model performance. The aggregation mechanism of augmentation strategies and graph learning models are also discussed by different application scenarios, i.e., data-specific, model-specific, and hybrid scenarios. To better show the outperformance of GAL, we experimentally validate the effectiveness and adaptability of different GAL strategies in different downstream tasks. Finally, we share our insights on several open issues of GAL, including heterogeneity, spatio-temporal dynamics, scalability, and generalization. © 2022 ACM.
- Authors: Yu, Shuo , Huang, Huafei , Dao, Minh , Xia, Feng
- Date: 2022
- Type: Text , Conference paper
- Relation: 31st ACM Web Conference, WWW 2022, Virtual, online, 25 April 2022, WWW 2022 - Companion Proceedings of the Web Conference 2022 p. 1063-1072
- Full Text:
- Reviewed:
- Description: Graph Augmentation Learning (GAL) provides outstanding solutions for graph learning in handling incomplete data, noise data, etc. Numerous GAL methods have been proposed for graph-based applications such as social network analysis and traffic flow forecasting. However, the underlying reasons for the effectiveness of these GAL methods are still unclear. As a consequence, how to choose optimal graph augmentation strategy for a certain application scenario is still in black box. There is a lack of systematic, comprehensive, and experimentally validated guideline of GAL for scholars. Therefore, in this survey, we in-depth review GAL techniques from macro (graph), meso (subgraph), and micro (node/edge) levels. We further detailedly illustrate how GAL enhance the data quality and the model performance. The aggregation mechanism of augmentation strategies and graph learning models are also discussed by different application scenarios, i.e., data-specific, model-specific, and hybrid scenarios. To better show the outperformance of GAL, we experimentally validate the effectiveness and adaptability of different GAL strategies in different downstream tasks. Finally, we share our insights on several open issues of GAL, including heterogeneity, spatio-temporal dynamics, scalability, and generalization. © 2022 ACM.
Deep video anomaly detection : opportunities and challenges
- Ren, Jing, Xia, Feng, Liu, Yemeng, Lee, Ivan
- Authors: Ren, Jing , Xia, Feng , Liu, Yemeng , Lee, Ivan
- Date: 2021
- Type: Text , Conference paper
- Relation: 21st IEEE International Conference on Data Mining Workshops, ICDMW 2021, Virtual, Online 7-10 December 2021, IEEE International Conference on Data Mining Workshops, ICDMW Vol. 2021-December, p. 959-966
- Full Text:
- Reviewed:
- Description: Anomaly detection is a popular and vital task in various research contexts, which has been studied for several decades. To ensure the safety of people's lives and assets, video surveillance has been widely deployed in various public spaces, such as crossroads, elevators, hospitals, banks, and even in private homes. Deep learning has shown its capacity in a number of domains, ranging from acoustics, images, to natural language processing. However, it is non-trivial to devise intelligent video anomaly detection systems cause anomalies significantly differ from each other in different application scenarios. There are numerous advantages if such intelligent systems could be realised in our daily lives, such as saving human resources in a large degree, reducing financial burden on the government, and identifying the anomalous behaviours timely and accurately. Recently, many studies on extending deep learning models for solving anomaly detection problems have emerged, resulting in beneficial advances in deep video anomaly detection techniques. In this paper, we present a comprehensive review of deep learning-based methods to detect the video anomalies from a new perspective. Specifically, we summarise the opportunities and challenges of deep learning models on video anomaly detection tasks, respectively. We put forth several potential future research directions of intelligent video anomaly detection system in various application domains. Moreover, we summarise the characteristics and technical problems in current deep learning methods for video anomaly detection. © 2021 IEEE.
- Authors: Ren, Jing , Xia, Feng , Liu, Yemeng , Lee, Ivan
- Date: 2021
- Type: Text , Conference paper
- Relation: 21st IEEE International Conference on Data Mining Workshops, ICDMW 2021, Virtual, Online 7-10 December 2021, IEEE International Conference on Data Mining Workshops, ICDMW Vol. 2021-December, p. 959-966
- Full Text:
- Reviewed:
- Description: Anomaly detection is a popular and vital task in various research contexts, which has been studied for several decades. To ensure the safety of people's lives and assets, video surveillance has been widely deployed in various public spaces, such as crossroads, elevators, hospitals, banks, and even in private homes. Deep learning has shown its capacity in a number of domains, ranging from acoustics, images, to natural language processing. However, it is non-trivial to devise intelligent video anomaly detection systems cause anomalies significantly differ from each other in different application scenarios. There are numerous advantages if such intelligent systems could be realised in our daily lives, such as saving human resources in a large degree, reducing financial burden on the government, and identifying the anomalous behaviours timely and accurately. Recently, many studies on extending deep learning models for solving anomaly detection problems have emerged, resulting in beneficial advances in deep video anomaly detection techniques. In this paper, we present a comprehensive review of deep learning-based methods to detect the video anomalies from a new perspective. Specifically, we summarise the opportunities and challenges of deep learning models on video anomaly detection tasks, respectively. We put forth several potential future research directions of intelligent video anomaly detection system in various application domains. Moreover, we summarise the characteristics and technical problems in current deep learning methods for video anomaly detection. © 2021 IEEE.
DQN-based resource allocation for NOMA-MEC-aided multi-source data stream
- Ling, Jing, Xia, Junjuan, Zhu, Fusheng, Gao, Chongzhi, Lai, Shiwei, Balasubramanian, Venki
- Authors: Ling, Jing , Xia, Junjuan , Zhu, Fusheng , Gao, Chongzhi , Lai, Shiwei , Balasubramanian, Venki
- Date: 2023
- Type: Text , Journal article
- Relation: Eurasip Journal on Advances in Signal Processing Vol. 2023, no. 1 (2023), p.
- Full Text:
- Reviewed:
- Description: This paper investigates a non-orthogonal multiple access (NOMA)-aided mobile edge computing (MEC) network with multiple sources and one computing access point (CAP), in which NOMA technology is applied to transmit multi-source data streams to CAP for computing. To measure the performance of the considered NOMA-aided MEC network, we first design the system cost as a linear weighting function of energy consumption and delay under the NOMA-aided MEC network. Moreover, we propose a deep Q network (DQN)-based offloading strategy to minimize the system cost by jointly optimizing the offloading ratio and transmission power allocation. Finally, we design experiments to demonstrate the effectiveness of the proposed strategy. Specifically, the designed strategy can decrease the system cost by about 15% compared with local computing when the number of sources is 5. © 2023, The Author(s).
- Authors: Ling, Jing , Xia, Junjuan , Zhu, Fusheng , Gao, Chongzhi , Lai, Shiwei , Balasubramanian, Venki
- Date: 2023
- Type: Text , Journal article
- Relation: Eurasip Journal on Advances in Signal Processing Vol. 2023, no. 1 (2023), p.
- Full Text:
- Reviewed:
- Description: This paper investigates a non-orthogonal multiple access (NOMA)-aided mobile edge computing (MEC) network with multiple sources and one computing access point (CAP), in which NOMA technology is applied to transmit multi-source data streams to CAP for computing. To measure the performance of the considered NOMA-aided MEC network, we first design the system cost as a linear weighting function of energy consumption and delay under the NOMA-aided MEC network. Moreover, we propose a deep Q network (DQN)-based offloading strategy to minimize the system cost by jointly optimizing the offloading ratio and transmission power allocation. Finally, we design experiments to demonstrate the effectiveness of the proposed strategy. Specifically, the designed strategy can decrease the system cost by about 15% compared with local computing when the number of sources is 5. © 2023, The Author(s).
Acupuncture for comorbid depression and insomnia in perimenopause : a feasibility patient-assessor-blinded, randomized, and sham-controlled clinical trial
- Zhao, Fei, Zheng, Zhen, Fu, Qiang-Qiang, Conduit, Russell, Xu, Hong, Wang, Hui-ru, Huang, Yu-Ling, Jiang, Ting, Zhang, Wen-Jing, Kennedy, Gerard
- Authors: Zhao, Fei , Zheng, Zhen , Fu, Qiang-Qiang , Conduit, Russell , Xu, Hong , Wang, Hui-ru , Huang, Yu-Ling , Jiang, Ting , Zhang, Wen-Jing , Kennedy, Gerard
- Date: 2023
- Type: Text , Journal article
- Relation: Frontiers in Public Health Vol. 11, no. (2023), p.
- Full Text:
- Reviewed:
- Description: Background and objective: Whilst acupuncture is widely used for treating psychosomatic diseases, there is little high-quality evidence supporting its application in comorbid perimenopausal depression (PMD) and insomnia (PMI) which are common complaints during climacteric. This feasibility, patient-assessor-blinded, randomized, sham-controlled clinical trial addresses this gap by investigating the efficacy and safety of acupuncture on depressed mood and poor sleep in women with comorbid PMD and PMI. Methods: Seventy eligible participants were randomly assigned to either real-acupuncture (RA) or sham-acupuncture (SA) groups. Either RA or SA treatment were delivered in 17 sessions over 8 weeks. The primary outcomes for mood and sleep were changes on 17-items Hamilton Depression Rating Scale (HAM-D17) and Pittsburgh Sleep Quality Index (PSQI) scores, from baseline to 16-week follow-up. Secondary outcome measures involved anxiety symptoms, perimenopausal symptoms, quality of life, participants' experience of and satisfaction with the acupuncture treatment. Blood samples were taken to measure reproductive hormone levels. Intention-To-Treat and Per-Protocol analyses were conducted with linear mixed-effects models. The James' and Bang's blinding indices were used to assess the adequacy of blinding. Results: Sixty-five participants completed all treatment sessions, and 54 and 41 participants completed the eight- and 16-week follow-ups, respectively. At post-treatment and 8-week follow-up, the RA group showed a significantly greater reduction in PSQI scores than the SA group did; although the reduction of HAM-D17 scores in RA group was significant, the change was not statistically different from that of SA. There were no significant mean differences between baseline and 16-week follow-up in either HAM-D17 or PSQI in either group. There were no significant between-group differences in serum reproductive hormone levels. All treatments were tolerable and no serious adverse events were reported, and the blinding was successful. Conclusion: Acupuncture is safe and can contribute to clinically relevant improvements in comorbid PMD and PMI, with satisfactory short-and medium-term effects. Whether the anti-depressive benefit of acupuncture is specific or non-specific remains to be determined. No evidence was found for any longer-term benefit of acupuncture compared to sham at 16 weeks. Further research is required to elucidate mechanisms underlying the short to medium term effects of acupuncture. Copyright © 2023 Zhao, Zheng, Fu, Conduit, Xu, Wang, Huang, Jiang, Zhang and Kennedy.
- Authors: Zhao, Fei , Zheng, Zhen , Fu, Qiang-Qiang , Conduit, Russell , Xu, Hong , Wang, Hui-ru , Huang, Yu-Ling , Jiang, Ting , Zhang, Wen-Jing , Kennedy, Gerard
- Date: 2023
- Type: Text , Journal article
- Relation: Frontiers in Public Health Vol. 11, no. (2023), p.
- Full Text:
- Reviewed:
- Description: Background and objective: Whilst acupuncture is widely used for treating psychosomatic diseases, there is little high-quality evidence supporting its application in comorbid perimenopausal depression (PMD) and insomnia (PMI) which are common complaints during climacteric. This feasibility, patient-assessor-blinded, randomized, sham-controlled clinical trial addresses this gap by investigating the efficacy and safety of acupuncture on depressed mood and poor sleep in women with comorbid PMD and PMI. Methods: Seventy eligible participants were randomly assigned to either real-acupuncture (RA) or sham-acupuncture (SA) groups. Either RA or SA treatment were delivered in 17 sessions over 8 weeks. The primary outcomes for mood and sleep were changes on 17-items Hamilton Depression Rating Scale (HAM-D17) and Pittsburgh Sleep Quality Index (PSQI) scores, from baseline to 16-week follow-up. Secondary outcome measures involved anxiety symptoms, perimenopausal symptoms, quality of life, participants' experience of and satisfaction with the acupuncture treatment. Blood samples were taken to measure reproductive hormone levels. Intention-To-Treat and Per-Protocol analyses were conducted with linear mixed-effects models. The James' and Bang's blinding indices were used to assess the adequacy of blinding. Results: Sixty-five participants completed all treatment sessions, and 54 and 41 participants completed the eight- and 16-week follow-ups, respectively. At post-treatment and 8-week follow-up, the RA group showed a significantly greater reduction in PSQI scores than the SA group did; although the reduction of HAM-D17 scores in RA group was significant, the change was not statistically different from that of SA. There were no significant mean differences between baseline and 16-week follow-up in either HAM-D17 or PSQI in either group. There were no significant between-group differences in serum reproductive hormone levels. All treatments were tolerable and no serious adverse events were reported, and the blinding was successful. Conclusion: Acupuncture is safe and can contribute to clinically relevant improvements in comorbid PMD and PMI, with satisfactory short-and medium-term effects. Whether the anti-depressive benefit of acupuncture is specific or non-specific remains to be determined. No evidence was found for any longer-term benefit of acupuncture compared to sham at 16 weeks. Further research is required to elucidate mechanisms underlying the short to medium term effects of acupuncture. Copyright © 2023 Zhao, Zheng, Fu, Conduit, Xu, Wang, Huang, Jiang, Zhang and Kennedy.
- Wu, Zhiyou, Quan, Jing, Li, G. Q., Tian, Jing
- Authors: Wu, Zhiyou , Quan, Jing , Li, G. Q. , Tian, Jing
- Date: 2011
- Type: Text , Journal article
- Relation: Journal of Optimization Theory and Applications Vol. , no. (2011), p. 1-28
- Full Text: false
- Reviewed:
- Description: Multivariate cubic polynomial optimization problems, as a special case of the general polynomial optimization, have a lot of practical applications in real world. In this paper, some necessary local optimality conditions and some necessary global optimality conditions for cubic polynomial optimization problems with mixed variables are established. Then some local optimization methods, including weakly local optimization methods for general problems with mixed variables and strongly local optimization methods for cubic polynomial optimization problems with mixed variables, are proposed by exploiting these necessary local optimality conditions and necessary global optimality conditions. A global optimization method is proposed for cubic polynomial optimization problems by combining these local optimization methods together with some auxiliary functions. Some numerical examples are also given to illustrate that these approaches are very efficient. © 2011 Springer Science+Business Media, LLC.
Optimality conditions and optimization methods for quartic polynomial optimization
- Wu, Zhiyou, Tian, Jing, Quan, Jing, Ugon, Julien
- Authors: Wu, Zhiyou , Tian, Jing , Quan, Jing , Ugon, Julien
- Date: 2014
- Type: Text , Journal article
- Relation: Applied Mathematics and Computation Vol. 232, no. (2014), p. 968-982
- Full Text: false
- Reviewed:
- Description: In this paper multivariate quartic polynomial optimization program (QPOP) is considered. Quartic optimization problems arise in various practical applications and are proved to be NP hard. We discuss necessary global optimality conditions for quartic problem (QPOP). And then we present a new (strongly or ε-strongly) local optimization method according to necessary global optimality conditions, which may escape and improve some KKT points. Finally we design a global optimization method for problem (QPOP) by combining the new (strongly or ε-strongly) local optimization method and an auxiliary function. Numerical examples show that our algorithms are efficient and stable.
Matching algorithms : fundamentals, applications and challenges
- Ren, Jing, Xia, Feng, Chen, Xiangtai, Liu, Jiaying, Sultanova, Nargiz
- Authors: Ren, Jing , Xia, Feng , Chen, Xiangtai , Liu, Jiaying , Sultanova, Nargiz
- Date: 2021
- Type: Text , Journal article , Review
- Relation: IEEE Transactions on Emerging Topics in Computational Intelligence Vol. 5, no. 3 (2021), p. 332-350
- Full Text:
- Reviewed:
- Description: Matching plays a vital role in the rational allocation of resources in many areas, ranging from market operation to people's daily lives. In economics, the term matching theory is coined for pairing two agents in a specific market to reach a stable or optimal state. In computer science, all branches of matching problems have emerged, such as the question-answer matching in information retrieval, user-item matching in a recommender system, and entity-relation matching in the knowledge graph. A preference list is the core element during a matching process, which can either be obtained directly from the agents or generated indirectly by prediction. Based on the preference list access, matching problems are divided into two categories, i.e., explicit matching and implicit matching. In this paper, we first introduce the matching theory's basic models and algorithms in explicit matching. The existing methods for coping with various matching problems in implicit matching are reviewed, such as retrieval matching, user-item matching, entity-relation matching, and image matching. Furthermore, we look into representative applications in these areas, including marriage and labor markets in explicit matching and several similarity-based matching problems in implicit matching. Finally, this survey paper concludes with a discussion of open issues and promising future directions in the field of matching. © 2017 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Jing Ren, Xia Feng, Nargiz Sultanova" is provided in this record**
- Authors: Ren, Jing , Xia, Feng , Chen, Xiangtai , Liu, Jiaying , Sultanova, Nargiz
- Date: 2021
- Type: Text , Journal article , Review
- Relation: IEEE Transactions on Emerging Topics in Computational Intelligence Vol. 5, no. 3 (2021), p. 332-350
- Full Text:
- Reviewed:
- Description: Matching plays a vital role in the rational allocation of resources in many areas, ranging from market operation to people's daily lives. In economics, the term matching theory is coined for pairing two agents in a specific market to reach a stable or optimal state. In computer science, all branches of matching problems have emerged, such as the question-answer matching in information retrieval, user-item matching in a recommender system, and entity-relation matching in the knowledge graph. A preference list is the core element during a matching process, which can either be obtained directly from the agents or generated indirectly by prediction. Based on the preference list access, matching problems are divided into two categories, i.e., explicit matching and implicit matching. In this paper, we first introduce the matching theory's basic models and algorithms in explicit matching. The existing methods for coping with various matching problems in implicit matching are reviewed, such as retrieval matching, user-item matching, entity-relation matching, and image matching. Furthermore, we look into representative applications in these areas, including marriage and labor markets in explicit matching and several similarity-based matching problems in implicit matching. Finally, this survey paper concludes with a discussion of open issues and promising future directions in the field of matching. © 2017 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Jing Ren, Xia Feng, Nargiz Sultanova" is provided in this record**
Global optimality conditions for some classes of polynomial integer programming problems
- Quan, Jing, Wu, Zhiyou, Li, Guoquan
- Authors: Quan, Jing , Wu, Zhiyou , Li, Guoquan
- Date: 2011
- Type: Text , Journal article
- Relation: Journal of Industrial and Management Optimization Vol. 7, no. 1 (2011), p. 67-78
- Full Text:
- Reviewed:
- Description: In this paper, some verifiable necessary global optimality conditions and sufficient global optimality conditions for some classes of polynomial integer programming problems are established. The relationships between these necessary global optimality conditions and these sufficient global optimality conditions are also discussed. The main theoretical tool for establishing these optimality conditions is abstract convexity.
- Authors: Quan, Jing , Wu, Zhiyou , Li, Guoquan
- Date: 2011
- Type: Text , Journal article
- Relation: Journal of Industrial and Management Optimization Vol. 7, no. 1 (2011), p. 67-78
- Full Text:
- Reviewed:
- Description: In this paper, some verifiable necessary global optimality conditions and sufficient global optimality conditions for some classes of polynomial integer programming problems are established. The relationships between these necessary global optimality conditions and these sufficient global optimality conditions are also discussed. The main theoretical tool for establishing these optimality conditions is abstract convexity.
- Authors: Pan, Heping
- Date: 2003
- Type: Text , Conference paper
- Relation: Paper presented at the 2003 Hawaii International Conference on Statistics and Related Fields, Hawaii, USA : 5th May, 2003
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000373
The role of acupuncture in the management of insomnia as a major or residual symptom among patients with active or previous depression : a systematic review and meta-analysis
- Zhao, Fei-Yi, Kennedy, Gerard, Spencer, Sarah, Conduit, Russell, Zhang, Wen-Jing, Fu, Qiang-Qiang, Zheng, Zhen
- Authors: Zhao, Fei-Yi , Kennedy, Gerard , Spencer, Sarah , Conduit, Russell , Zhang, Wen-Jing , Fu, Qiang-Qiang , Zheng, Zhen
- Date: 2022
- Type: Text , Journal article , Review
- Relation: Frontiers in Psychiatry Vol. 13, no. (2022), p.
- Full Text:
- Reviewed:
- Description: Background: Due to concerns about risks associated with antidepressants and/or hypnotics, complementary therapies such as acupuncture have been sought by patients with active or previous depression to manage insomnia. This systematic review aimed to clarify if acupuncture is effective and safe enough to be recommended as an alternative or adjuvant therapy to standard care in ameliorating concomitant or residual insomnia, two types of insomnia associated with depression. Methods: Randomized controlled trials (RCTs) of depression-related insomnia (DI) treatment via acupuncture vs. waitlist-control or placebo-/sham-acupuncture and RCTs of DI treatment via acupuncture alone or combined with standard care [Western pharmacotherapy and/or cognitive-behavioral therapy (CBT)] vs. standard care alone were searched for from seven databases from inception to December 2021. Cochrane criteria were followed. Results: Twenty-one studies involving 1,571 participants were analyzed. For insomnia as a major symptom of active depression, meta-analyses suggested that acupuncture significantly reduced the global scores of both the Pittsburg Sleep Quality Index (PSQI) [MD = −3.12, 95% CI (−5.16, −1.08), p < 0.01] and Hamilton Depression Scale (HAMD) [SMD = −2.67, 95% CI (−3.51, −1.84), p < 0.01], in comparison with placebo-acupuncture. When compared with conventional pharmacotherapy (antidepressants and/or hypnotics), the results favored acupuncture in decreasing PSQI [MD = −1.17, 95% CI (−2.26, −0.08), p = 0.03] and HAMD [SMD = −0.47, 95% CI (−0.91, −0.02), p = 0.04]. Acupuncture was comparable to conventional pharmacotherapy in reducing scores of each domain of PSQI. For insomnia as a residual symptom of previous or partially remitted depression, acupuncture conferred a very limited, non-significant therapeutic advantage against sham-/placebo-acupuncture. Whether acupuncture has an add-on effect to conventional pharmacotherapy in this type of insomnia has not been investigated. Also, no study was available to address the efficacy differences between acupuncture and CBT or the synergistic effect of these two therapies. Conclusions: There is a low to moderate level of evidence supporting acupuncture as a safe and effective remedy alternative to or adjuvant to conventional pharmacotherapy (antidepressant and/or hypnotic) in improving insomnia and other depression symptoms among patients with active depression. Furthermore, the patients' complaint of disrupted sleep continuity is most likely to benefit from acupuncture. The benefit of acupuncture on residual insomnia associated with previous or partially remitted depression is limited. Future acupuncture studies need to consider applying optimal dosage and addressing deficiencies in trial quality. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021269880, PROSPERO, identifier: CRD42021269880. Copyright © 2022 Zhao, Kennedy, Spencer, Conduit, Zhang, Fu and Zheng.
- Authors: Zhao, Fei-Yi , Kennedy, Gerard , Spencer, Sarah , Conduit, Russell , Zhang, Wen-Jing , Fu, Qiang-Qiang , Zheng, Zhen
- Date: 2022
- Type: Text , Journal article , Review
- Relation: Frontiers in Psychiatry Vol. 13, no. (2022), p.
- Full Text:
- Reviewed:
- Description: Background: Due to concerns about risks associated with antidepressants and/or hypnotics, complementary therapies such as acupuncture have been sought by patients with active or previous depression to manage insomnia. This systematic review aimed to clarify if acupuncture is effective and safe enough to be recommended as an alternative or adjuvant therapy to standard care in ameliorating concomitant or residual insomnia, two types of insomnia associated with depression. Methods: Randomized controlled trials (RCTs) of depression-related insomnia (DI) treatment via acupuncture vs. waitlist-control or placebo-/sham-acupuncture and RCTs of DI treatment via acupuncture alone or combined with standard care [Western pharmacotherapy and/or cognitive-behavioral therapy (CBT)] vs. standard care alone were searched for from seven databases from inception to December 2021. Cochrane criteria were followed. Results: Twenty-one studies involving 1,571 participants were analyzed. For insomnia as a major symptom of active depression, meta-analyses suggested that acupuncture significantly reduced the global scores of both the Pittsburg Sleep Quality Index (PSQI) [MD = −3.12, 95% CI (−5.16, −1.08), p < 0.01] and Hamilton Depression Scale (HAMD) [SMD = −2.67, 95% CI (−3.51, −1.84), p < 0.01], in comparison with placebo-acupuncture. When compared with conventional pharmacotherapy (antidepressants and/or hypnotics), the results favored acupuncture in decreasing PSQI [MD = −1.17, 95% CI (−2.26, −0.08), p = 0.03] and HAMD [SMD = −0.47, 95% CI (−0.91, −0.02), p = 0.04]. Acupuncture was comparable to conventional pharmacotherapy in reducing scores of each domain of PSQI. For insomnia as a residual symptom of previous or partially remitted depression, acupuncture conferred a very limited, non-significant therapeutic advantage against sham-/placebo-acupuncture. Whether acupuncture has an add-on effect to conventional pharmacotherapy in this type of insomnia has not been investigated. Also, no study was available to address the efficacy differences between acupuncture and CBT or the synergistic effect of these two therapies. Conclusions: There is a low to moderate level of evidence supporting acupuncture as a safe and effective remedy alternative to or adjuvant to conventional pharmacotherapy (antidepressant and/or hypnotic) in improving insomnia and other depression symptoms among patients with active depression. Furthermore, the patients' complaint of disrupted sleep continuity is most likely to benefit from acupuncture. The benefit of acupuncture on residual insomnia associated with previous or partially remitted depression is limited. Future acupuncture studies need to consider applying optimal dosage and addressing deficiencies in trial quality. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021269880, PROSPERO, identifier: CRD42021269880. Copyright © 2022 Zhao, Kennedy, Spencer, Conduit, Zhang, Fu and Zheng.
Web of scholars : a scholar knowledge graph
- Liu, Jiaying, Ren, Jing, Zheng, Wenqing, Chi, Lianhua, Lee, Ivan, Xia, Feng
- Authors: Liu, Jiaying , Ren, Jing , Zheng, Wenqing , Chi, Lianhua , Lee, Ivan , Xia, Feng
- Date: 2020
- Type: Text , Conference paper
- Relation: 43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020 p. 2153-2156
- Full Text:
- Reviewed:
- Description: In this work, we demonstrate a novel system, namely Web of Scholars, which integrates state-of-the-art mining techniques to search, mine, and visualize complex networks behind scholars in the field of Computer Science. Relying on the knowledge graph, it provides services for fast, accurate, and intelligent semantic querying as well as powerful recommendations. In addition, in order to realize information sharing, it provides open API to be served as the underlying architecture for advanced functions. Web of Scholars takes advantage of knowledge graph, which means that it will be able to access more knowledge if more search exist. It can be served as a useful and interoperable tool for scholars to conduct in-depth analysis within Science of Science. © 2020 ACM.
- Authors: Liu, Jiaying , Ren, Jing , Zheng, Wenqing , Chi, Lianhua , Lee, Ivan , Xia, Feng
- Date: 2020
- Type: Text , Conference paper
- Relation: 43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020 p. 2153-2156
- Full Text:
- Reviewed:
- Description: In this work, we demonstrate a novel system, namely Web of Scholars, which integrates state-of-the-art mining techniques to search, mine, and visualize complex networks behind scholars in the field of Computer Science. Relying on the knowledge graph, it provides services for fast, accurate, and intelligent semantic querying as well as powerful recommendations. In addition, in order to realize information sharing, it provides open API to be served as the underlying architecture for advanced functions. Web of Scholars takes advantage of knowledge graph, which means that it will be able to access more knowledge if more search exist. It can be served as a useful and interoperable tool for scholars to conduct in-depth analysis within Science of Science. © 2020 ACM.
Towards a low complexity scheme for medical images in scalable video coding
- Shoaib, Muhammad, Imran, Muhammad, Subhan, Fazli, Ahmad, Iftikhar
- Authors: Shoaib, Muhammad , Imran, Muhammad , Subhan, Fazli , Ahmad, Iftikhar
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 41439-41451
- Full Text:
- Reviewed:
- Description: Medical imaging has become of vital importance for diagnosing diseases and conducting noninvasive procedures. Advances in eHealth applications are challenged by the fact that Digital Imaging and Communications in Medicine (DICOM) requires high-resolution images, thereby increasing their size and the associated computational complexity, particularly when these images are communicated over IP and wireless networks. Therefore, medical research requires an efficient coding technique to achieve high-quality and low-complexity images with error-resilient features. In this study, we propose an improved coding scheme that exploits the content features of encoded videos with low complexity combined with flexible macroblock ordering for error resilience. We identify the homogeneous region in which the search for optimal macroblock modes is early terminated. For non-homogeneous regions, the integration of smaller blocks is employed only if the vector difference is less than the threshold. Results confirm that the proposed technique achieves a considerable performance improvement compared with existing schemes in terms of reducing the computational complexity without compromising the bit-rate and peak signal-to-noise ratio. © 2013 IEEE.
- Authors: Shoaib, Muhammad , Imran, Muhammad , Subhan, Fazli , Ahmad, Iftikhar
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 41439-41451
- Full Text:
- Reviewed:
- Description: Medical imaging has become of vital importance for diagnosing diseases and conducting noninvasive procedures. Advances in eHealth applications are challenged by the fact that Digital Imaging and Communications in Medicine (DICOM) requires high-resolution images, thereby increasing their size and the associated computational complexity, particularly when these images are communicated over IP and wireless networks. Therefore, medical research requires an efficient coding technique to achieve high-quality and low-complexity images with error-resilient features. In this study, we propose an improved coding scheme that exploits the content features of encoded videos with low complexity combined with flexible macroblock ordering for error resilience. We identify the homogeneous region in which the search for optimal macroblock modes is early terminated. For non-homogeneous regions, the integration of smaller blocks is employed only if the vector difference is less than the threshold. Results confirm that the proposed technique achieves a considerable performance improvement compared with existing schemes in terms of reducing the computational complexity without compromising the bit-rate and peak signal-to-noise ratio. © 2013 IEEE.