243 research outputs found
Correction: The relative age effect on fundamental movement skills in Chinese children aged 3–5 years
No full textFollowing publication of the original article [1], the authors reported the following error In the article title, “skillsl” should be “skills” Kai Li, Shijie Liu and Yujun Cai's author unit information needs to be adjusted to:School of Physical Education, ShanghaiUniversity of Sport, Shanghai, China. The author unit information for Jiani Ma needs to be adjusted to:Research Centre for Sport, Exercise and Life Sciences, Coventry University, Coventry, UKSchool of Health and Social Development, Deakin University, Geelong, AustraliaInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia In the article title, “skillsl” should be “skills” Kai Li, Shijie Liu and Yujun Cai's author unit information needs to be adjusted to: School of Physical Education, ShanghaiUniversity of Sport, Shanghai, China. School of Physical Education, ShanghaiUniversity of Sport, Shanghai, China. The author unit information for Jiani Ma needs to be adjusted to: Research Centre for Sport, Exercise and Life Sciences, Coventry University, Coventry, UK School of Health and Social Development, Deakin University, Geelong, Australia Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia Research Centre for Sport, Exercise and Life Sciences, Coventry University, Coventry, UK School of Health and Social Development, Deakin University, Geelong, Australia Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia The article title and affiliations has been updated above and the original article has been corrected.</p
Experimental Study on Machine Learning with Approximation to Data Streams
No full textRealtime transferring of data streams enables many data analytics and machine learning applications in the areas of e.g. massive IoT and industrial automation. Big data volume of those streams is a significant burden or overhead not only to the transportation network, but also to the corresponding application servers. Therefore, researchers and scientists focus on reducing the amount of data needed to be transferred via data compressions and approximations. Data compression techniques like lossy compression can significantly reduce data volume with the price of data information loss. Meanwhile, how to do data compression is highly dependent on the corresponding applications. However, when apply the decompressed data in some data analysis application like machine learning, the results may be affected due to the information loss. In this paper, the author did a study on the impact of data compression to the machine learning applications. In particular, from the experimental perspective, it shows the tradeoff among the approximation error bound, compression ratio and the prediction accuracy of multiple machine learning methods. The author believes that, with proper choice, data compression can dramatically reduce the amount of data transferred with limited impact on the machine learning applications.Realtidsöverföring av dataströmmar möjliggör många dataanalyser och maskininlärningsapplikationer inom områdena t.ex. massiv IoT och industriell automatisering. Stor datavolym för dessa strömmar är en betydande börda eller omkostnad inte bara för transportnätet utan också för motsvarande applikationsservrar. Därför fokuserar forskare och forskare om att minska mängden data som behövs för att överföras via datakomprimeringar och approximationer. Datakomprimeringstekniker som förlustkomprimering kan minska datavolymen betydligt med priset för datainformation. Samtidigt är datakomprimering mycket beroende av motsvarande applikationer. Men när du använder dekomprimerade data i en viss dataanalysapplikation som maskininlärning, kan resultaten påverkas på grund av informationsförlusten. I denna artikel gjorde författaren en studie om effekterna av datakomprimering på maskininlärningsapplikationerna. I synnerhet, från det experimentella perspektivet, visar det avvägningen mellan tillnärmningsfelbundet, kompressionsförhållande och förutsägbarhetsnoggrannheten för flera maskininlärningsmetoder. Författaren anser att datakomprimering med rätt val dramatiskt kan minska mängden data som överförs med begränsad inverkan på maskininlärningsapplikationerna
Monitoring the crowd of people by deep learning enabled image analytics
No full textThere is a great demand for crowd counting in some practical applications nowadays, such as traffic monitoring, traffic management, sports events and political meetings. In some cases, it is extremely important to obtain information on the number of people. In recent years, many methods and network models for calculating population density have been proposed and made significant progress. However, due to the uneven distribution, high congestion, chaos and occlusion, the effect of the traditional method is not ideal. And the display of the density map is more suitable to meet the demand of real applications. The convolutional neural network can perform well regression and a density map of crowd can be generated by taking the entire image as the input. Based on this method, the functions of accurate crowd statistics and high-quality density map generation are researched and implemented in this project, and a crowd monitoring system based on deep machine learning was developed.Master of Science (Signal Processing
A DESCRIPTIVE STUDY OF DEPENDENT AND INDEPENDENT PERSONALITY CHARACTERISTICS AMONG PSU SINGLETON AND NON-SINGLETON STUDENTS
Get PDFThis descriptive study was designed to explore, describe, and compare singleton and non-singleton Pittsburg State University Chinese students, who self-reported their independent and dependent personality characteristics. Data for this study were obtained from a survey instrument developed by this investigator and administrated to volunteer Chinese students (Mainland or Taiwan) enrolled in 2010 fall semester at Pittsburg State University. Participation was voluntary and anonymity was assured. No statistically significant differences were found in independent and dependent personality characteristics among singleton and non-singleton Chinese college students at Pittsburg State University. Conclusions were that the findings from the present study were consistent with prior research conducted in China. Jiang and Yao (2010) and Ye (2010) concluded that the development of certain personality, cognitive, emotional, and social differences are most pronounced with younger children, particularly in early childhood and in kindergarten. As only borns mature, differences overtime tend to become less pronounced or to become not significant
Starting to close the communication gap in Technology transfer to the PRC
No full textTitle: “Starting to close the communication gap in technology transfer to the PRC” Level: Final assignment for Master Degree in Business Administration Author: Jiani Yang, Zhouni Lin Supervisor: Ernst HOLLANDER Examiner: Akmal HYDER Date: 2012-May Purpose — We have double purpose of promoting SME’s involvement in PRC’s development and technology transfer for sustainability in this research. From the double perspective of Chinese business economics and long run cooperation with Swedish enterprises, we investigate and analysis the main problems faced by SMEs when taking technology transfer to China. By doing this to help SMEs to overcome the barriers during technology transfer and promote the international technology transfer cooperation in the long run, as well as appeal technology transfer agencies to adopt a holistic approach to help SMEs to plan and implement technology transfer projects effectively and sustainably. Design/methodology/approach — We use the technology transfer project in China’s sewage market as our research case to illustrate our research problems. The discussion is based on the existing literatures regarding technology transfer, former researches and authentic cases about technology transfer to China, and interviews with relevant people. Findings — The findings indicates there is huge potential business opportunities in China’s sewage treatment market. Information transparency plays a critical role to foster the cooperation between transferor and transfers, as well as promoting SME’s involvement in China. Get directly to the leader taking the decisions is one effective way to get access to China’s market in short term. Communication gap becomes one of the main concerns for SMEs when taking technology transfer to China. In mid-term, organize workshop, get to learn with the local employee, promote the understanding between each other; get to the person who is capable to understand the technology and its effect is necessary; For the long run cooperation, technology transfer process transparency needs to be improved. Originality/value — This paper is of value through draw out the fact of common problems of taking technology transfer to China’s sewage market and analysis the reason. Transparency problem during the technology transfer process is drawn and analyzed. Key points for accessing China’s market by SMEs are produced.
A Re-Reflection to Protection Standards of International Intellectual Property In the Context of Climate-Friendly Technology Transfer
No full textThere is an unsettled debate regarding the role of intellectual property (IP) in the development and transfer of climate friendly technologies under the international climate negotiation. Such debate arises from distinct opinions on IP protection standards. It can worsen the solution of climate-friendly technology transfer to developing countries. This study aims to address the question of whether a premise for minimum protection standards exists in the international IP system combined with climate-friendly technology transfer. First, the basic problem of why international IP standards pose a threat to climate-friendly technology transfer is clarified. Second, three levels of arguments are applied to prove that the IP protection standard is not the only minimum requirement. The negative effects on the transfer of climate-friendly technology arise from ambiguous existing legal provisions and practices. Third, this study provides some suggestions for improvement for international IP standards accommodating the transfer of climate-friendly technology
Brand Valuation in the PRC Market: Toward Understanding the Nuances in Consumers’ States of Mind
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Improving security in IoT-based human activity recognition: a correlation-based anomaly detection approach
No full textAnomaly detection in Human Activity Recognition (HAR) is a critical subfield that leverages data from the Internet of Things (IoT) to monitor human activities and detect errors or abnormal events. Conventional rule-based approaches often fail to capture the intricate relationships between sensor values, while machine learning-based methods tend to lack the ability to provide explainability and actionable context for the detected anomalies. In this paper, we introduce a novel correlation-based anomaly detection framework designed to improve the security and reliability of IoT-enabled HAR systems. Our proposed scheme utilizes a context-aware deep learning architecture to predict sensor values by leveraging the interdependencies between coexisting sensors in the deployment environment. Experimental results demonstrate that our model achieves a best anomaly prediction accuracy of 99.76% on individual sensors and outperforms other baseline models, consistently maintaining high F1 scores with a minimum of 0.866 on various sensors, even when the training dataset is reduced. Furthermore, we propose an AI-Generated Content (AIGC)-based visualization method for reporting anomalies, offering clear insights into the context and severity of detected anomalies and their potential system impact.AI SingaporeMinistry of Education (MOE)Nanyang Technological UniversityNational Research Foundation (NRF)Submitted/Accepted versionThis research is supported by the National Research Foundation, Singapore and Infocomm Media Development Authority under its Trust Tech Funding Initiative and Strategic Capability Research Centres Funding Initiative, Future Communications Research \& Development Programme, Defence Science Organisation (DSO) National Laboratories under the AI Singapore Programme (FCP-NTU-RG-2022-010 and FCP-ASTAR-TG-2022-003), Singapore Ministry of Education (MOE) Tier 1 (RG87/22), the NTU Centre for Computational Technologies in Finance (NTU-CCTF), and Seitee Pte Ltd. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of National Research Foundation, Singapore and Infocomm Media Development Authority. Jiani Fan's research is partly supported by Alibaba Group through Alibaba Innovative Research (AIR) Program and Alibaba-NTU Singapore Joint Research Institute (JRI), Nanyang Technological University, Singapore.This research is supported by the National Research Foundation, Singapore and Infocomm Media Development Authority under its Trust Tech Funding Initiative and Strategic Capability Research Centres Funding Initiative, Future Communications Research & Development Programme, Defence Science Organisation (DSO) National Laboratories under the AI Singapore Programme (FCP-NTU-RG-2022-010 and FCP-ASTARTG-2022-003), Singapore Ministry of Education (MOE) Tier 1 (RG87/22), the NTU Centre for Computational Technologies in Finance (NTU-CCTF), and Seitee Pte Ltd. Jiani Fan’s research is partly supported by Alibaba Group through Alibaba Innovative Research (AIR) Program and Alibaba-NTU Singapore Joint Research Institute (JRI), Nanyang Technological University, Singapore
Neighborhood Upgrading Catalyst: A renovation academy combined with a student hostel
No full textResidential educatio
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