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| 1 | Towards a Service-Oriented Architecture for a Mobile Assistive System with Real-time Environmental Sensing显示文摘With the growing aging population, age-related diseases have increased considerably over the years.In response to these, Ambient Assistive Living(AAL) systems are being developed and are continually evolving to enrich and support independent living. While most researchers investigate robust Activity Recognition(AR)techniques, this paper focuses on some of the architectural challenges of the AAL systems. This work proposes a system architecture that fuses varying software design patterns and integrates readily available hardware devices to create Wireless Sensor Networks(WSNs) for real-time applications. The system architecture brings together the Service-Oriented Architecture(SOA), semantic web technologies, and other methods to address some of the shortcomings of the preceding system implementations using off-the-shelf and open source components. In order to validate the proposed architecture, a prototype is developed and tested positively to recognize basic user activities in real time. The system provides a base that can be further extended in many areas of AAL systems,including composite AR. | Darpan Triboan Liming Chen Feng Chen Zumin Wang | 2016 | Tsinghua Science and Technology2016，21，6： | 2 |
| 2 | Risk of adverse outcomes associated with concomitant use of clopidogrel and proton pump inhibitors following acute coronary syndrome显示文摘 | Ekta GA Darpan BE John SA | 2009 | Dig Dis Sci2009，7，8： | 1 |
| 3 | Temporomandibular joint arthrocentesis for internal derangement with disc displacement without reduction显示文摘 | Darpan Bhargava Megha Jain | 2015 | Journal of maxillofacial and oral surgery2015，14，2： | 1 |
| 4 | Risk of Adverse Clinical Outcomes with Concomitant Use of Clopidogrel and Proton Pump Inhibitors Following Percutaneous Coronary Intervention显示文摘 | Ekta Gupta Darpan Bansal John Sotos Kevin Olden | 2010 | Digestive Diseases and Sciences2010，，7： | 1 |
| 5 | Xanthine oxidase inhibitors: a patent survey显示文摘 | Raj Kumar Darpan Sahil Sharma Rajveer Singh | 2011 | Expert Opinion on Therapeutic Patents2011，，7： | 1 |
| 6 | Keratocystic odontogenic tumour (KCOT)—a cyst to a tumour显示文摘 | Darpan Bhargava Ashwini Deshpande M. Anthony Pogrel | 2012 | Oral and Maxillofacial Surgery2012，，2： | 1 |
| 7 | Risk of Adverse Clinical Outcomes with Concomitant Use of Clopidogrel and Proton Pump Inhibitors Following Percutaneous Coronary Intervention显示文摘 | Ekta Gupta Darpan Bansal John Sotos Kevin Olden | 2010 | Digestive Diseases and Sciences2010，，7： | 1 |
| 8 | Xanthine oxidase inhibitors : a patent survey 显示文摘 | KUMAR R DARPAN SHARMA S | 2011 | Expert OpinTher Pat2011，21，7： | 1 |
| 9 | Risk of adverse outcomes associated with concomitant use of clopidogrel and proton pump inhibitors following acute coronary syn - drome 显示文摘 | Ekta GA Darpan BE John SA | 2009 | Dig Dis Sci2009，7，8： | 1 |
| 10 | Ferroptosis: An Iron-Dependent Form of Nonapoptotic Cell Death显示文摘 | Scott J. Dixon Kathryn M. Lemberg Michael R. Lamprecht Rachid Skouta Eleina M. Zaitsev Caroline E. Gleason Darpan N. Patel Andras J. Bauer Alexandra M. Cantley Wan Seok Yang Barclay Morrison Brent R. Stockwell | 2012 | Cell2012，，5： | 1 |
| 11 | Assessment of left ventricular function: comparison of cardiac multidetector-row computed tomography with two-dimension standard echocardiography for assessment of left ventricular function显示文摘 | Darpan Bansal Robin M. Singh Mrinalini Sarkar Ravi Sureddi Kelly C. Mcbreen Timothy Griffis Anjan Sinha Jawahar L. Mehta | 2008 | The International Journal of Cardiovascular Imaging2008，，3： | 1 |
| 12 | Optimal and Effective Resource Management in Edge Computing显示文摘Edge computing is a cloud computing extension where physical compu-ters are installed closer to the device to minimize latency.The task of edge data cen-ters is to include a growing abundance of applications with a small capability in comparison to conventional data centers.Under this framework,Federated Learning was suggested to offer distributed data training strategies by the coordination of many mobile devices for the training of a popular Artificial Intelligence(AI)model without actually revealing the underlying data,which is significantly enhanced in terms of privacy.Federated learning(FL)is a recently developed decentralized profound learning methodology,where customers train their localized neural network models independently using private data,and then combine a global model on the core server together.The models on the edge server use very little time since the edge server is highly calculated.But the amount of time it takes to download data from smartphone users on the edge server has a significant impact on the time it takes to complete a single cycle of FL operations.A machine learning strategic planning system that uses FL in conjunction to minimise model training time and total time utilisation,while recognising mobile appliance energy restrictions,is the focus of this study.To further speed up integration and reduce the amount of data,it implements an optimization agent for the establishment of optimal aggregation policy and asylum architecture with several employees’shared learners.The main solutions and lessons learnt along with the prospects are discussed.Experiments show that our method is superior in terms of the effective and elastic use of resources. | Darpan Majumder S.Mohan Kumar | 2023 | Computer Systems Science & Engineering2023，44，2： | 0 |
| 13 | Optimized Load Balancing Technique for Software Defined Network显示文摘Software-defined networking is one of the progressive and prominent innovations in Information and Communications Technology.It mitigates the issues that our conventional network was experiencing.However,traffic data generated by various applications is increasing day by day.In addition,as an organization’s digital transformation is accelerated,the amount of information to be processed inside the organization has increased explosively.It might be possible that a Software-Defined Network becomes a bottleneck and unavailable.Various models have been proposed in the literature to balance the load.However,most of the works consider only limited parameters and do not consider controller and transmission media loads.These loads also contribute to decreasing the performance of Software-Defined Networks.This work illustrates how a software-defined network can tackle the load at its software layer and give excellent results to distribute the load.We proposed a deep learning-dependent convolutional neural networkbased load balancing technique to handle a software-defined network load.The simulation results show that the proposed model requires fewer resources as compared to existing machine learning-based load balancing techniques. | Aashish Kumar Darpan Anand Sudan Jha Gyanendra Prasad Joshi Woong Cho | 2022 | Computers, Materials & Continua2022，，7： | 0 |
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