This volume contains the proceedings of EuroGP 2000, the European Conf- ence on Genetic Programming, held in Edinburgh on the 15th and 16th April 2000. This event was the third in a series which started with the two E...
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ISBN:
(数字)9783540462392
ISBN:
(纸本)9783540673392
This volume contains the proceedings of EuroGP 2000, the European Conf- ence on Genetic Programming, held in Edinburgh on the 15th and 16th April 2000. This event was the third in a series which started with the two European workshops: EuroGP’98, held in Paris in April 1998, and EuroGP’99, held in Gothenburg in May 1999. EuroGP 2000 was held in conjunction with EvoWo- shops 2000 (17th April) and ICES 2000 (17th-19th April). Genetic Programming (GP) is a growing branch of Evolutionary Compu- tion in which the structures in the population being evolved are computer p- grams. GP has been applied successfully to a large number of di?cult problems like automatic design, pattern recognition, robotic control, synthesis of neural networks, symbolic regression, music and picture generation, biomedical app- cations, etc. In recent years,even human-competitive results have been achieved by a number of groups. EuroGP 2000, the ?rst evolutionary computation conference of the new m- lennium, was the biggest event devoted to genetic programming to be held in Europe in 2000. It was a high quality conference where state-of-the-art work on the theory of GP and applications of GP to real world problems was presented.
This book gathers selected high-quality research papers presented at the 2nd International Conference on Advanced computing Applications (ICACA 2021), held virtually during 27––28 March 2021. The book is divided int...
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ISBN:
(数字)9789811652073
ISBN:
(纸本)9789811652066
This book gathers selected high-quality research papers presented at the 2nd International Conference on Advanced computing Applications (ICACA 2021), held virtually during 27––28 March 2021. The book is divided into four sections. These are communication and computing, signal processing and multimedia, computational intelligence and data analytics and decision computing. The topics covered are advanced communication technologies, IoT-based systems and applications, network security and reliability, virtualization technologies, compressed sensors and multimedia applications, signal image and video processing, machine learning, pattern recognitions, intelligent computing, big data analytics, analytics in bio-computing, AI-driven 6G mobile wireless networks and autonomous driving.
The advancement of the Internet of Medical Things (IoMT) has led to the emergence of various health and emotion care services, e.g., health monitoring. To cater to increasing computational requirements of IoMT service...
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The advancement of the Internet of Medical Things (IoMT) has led to the emergence of various health and emotion care services, e.g., health monitoring. To cater to increasing computational requirements of IoMT services, Mobile Edge computing (MEC) has emerged as an indispensable technology in smart health. Benefiting from the cost-effectiveness of deployment, unmanned aerial vehicles (UAVs) equipped with MEC servers in Non-Orthogonal Multiple Access (NOMA) have emerged as a promising solution for providing smart health services in proximity to medical devices (MDs). However, the escalating number of MDs and the limited availability of communication resources of UAVs give rise to a significant increase in transmission latency. Moreover, due to the limited communication range of UAVs, the geographically-distributed MDs lead to workload imbalance of UAVs, which deteriorates the service response delay. To this end, this paper proposes a UAV-enabled Distributed computation Offloading and Power control method with Multi-Agent, named DOPMA, for NOMA-based IoMT environment. Specifically, this paper introduces computation and transmission queue models to analyze the dynamic characteristics of task execution latency and energy consumption. Moreover, a credit assignment scheme-based reward function is designed considering both system-level rewards and rewards tailored to each MD, and an improved multi-agent deep deterministic policy gradient algorithm is developed to derive offloading and power control decisions independently. Extensive simulations demonstrate that the proposed method outperforms existing schemes, achieving \(7.1\%\) reduction in energy consumption and \(16\%\) decrease in average delay.
The Anchor-based Multi-view Subspace Clustering (AMSC) has turned into a favourable tool for large-scale multi-view clustering. However, there still exist some limitations to the current AMSC approaches. First, they t...
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The Anchor-based Multi-view Subspace Clustering (AMSC) has turned into a favourable tool for large-scale multi-view clustering. However, there still exist some limitations to the current AMSC approaches. First, they typically recover anchor graph structure in the original linear space, restricting their feasibility for nonlinear scenarios. Second, they usually overlook the potential benefits of jointly capturing the inter-view and intra-view information for enhancing the anchor representation learning. Third, these approaches mostly perform anchor-based subspace learning by a specific matrix norm, neglecting the latent high-order correlation across different views. To overcome these limitations, this paper presents an efficient and effective approach termed Large-scale Tensorized Multi-view Kernel Subspace Clustering (LTKMSC). Different from the existing AMSC approaches, our LTKMSC approach exploits both inter-view and intra-view awareness for anchor-based representation building. Concretely, the low-rank tensor learning is leveraged to capture the high-order correlation (i.e., the inter-view complementary information) among distinct views, upon which the \(l_{1,2}\) norm is imposed to explore the intra-view anchor graph structure in each view. Moreover, the kernel learning technique is leveraged to explore the nonlinear anchor-sample relationships embedded in multiple views. With the unified objective function formulated, an efficient optimization algorithm that enjoys low computational complexity is further designed. Extensive experiments on a variety of multi-view datasets have confirmed the efficiency and effectiveness of our approach when compared with the other competitive approaches.
This book features selected papers from the 6th International Conference on Mathematics and computing (ICMC 2020), organized by Sikkim University, Gangtok, Sikkim, India, during September 2020. It covers recent advanc...
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ISBN:
(数字)9789811580611
ISBN:
(纸本)9789811580604
This book features selected papers from the 6th International Conference on Mathematics and computing (ICMC 2020), organized by Sikkim University, Gangtok, Sikkim, India, during September 2020. It covers recent advances in the field of mathematics, statistics, and scientific computing. The book presents innovative work by leading academics, researchers, and experts from industry.
The study reported in this paper is an ongoing effort. We reported a preliminary analysis of the data in the paper. The current experiments varied the subjects to c- duct online group learning activities by the commun...
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ISBN:
(数字)9783540304814
ISBN:
(纸本)9783540238928
The study reported in this paper is an ongoing effort. We reported a preliminary analysis of the data in the paper. The current experiments varied the subjects to c- duct online group learning activities by the communication media such as email and threaded discussion. Although, we could have easily learned the impact of mobile devices in learning if we divided the subjects to use different hardware such as p- sonal computers, personal digital assistant, or mobile phones, we believe our findings will still be able to provide useful insights on the difficulties that the mobile learners will face in solving problems as a group. Our analysis result will also provide ba- line information on whether the traits of the successful or failed online groups are applicable to the mobile learners. For example, we expect the SMS will be a better medium to overcome the major problem of instant communication or the rapid propagation of the information as the mobile phones have built-in mechanism to remind the users of the incoming new messages and also the mobile phone users are expected to be interrupted for the incoming messages. However, we need further investigation of other problems, which hinder the optimum online group work. For example, ‘accuracy of the transferred information’ was identified as one of the pr- lems of using emails as the communication medium. Personal Digital Assistant (PDA) or SMS are more apt to deliver shorter messages than the typical emails.
This book constitutes the refereed conference proceedings of the 12th International Conference on Intelligent data Analysis, which was held in October 2013 in London, UK. The 36 revised full papers together with 3 inv...
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ISBN:
(数字)9783642413988
ISBN:
(纸本)9783642413971
This book constitutes the refereed conference proceedings of the 12th International Conference on Intelligent data Analysis, which was held in October 2013 in London, UK. The 36 revised full papers together with 3 invited papers were carefully reviewed and selected from 84 submissions handling all kinds of modeling and analysis methods, irrespective of discipline. The papers cover all aspects of intelligent data analysis, including papers on intelligent support for modeling and analyzing data from complex, dynamical systems.
This book constitutes the refereed proceedings of the 15th Asia-Pacific Conference APWeb 2013 held in Sydney, Australia, in April 2013.;The 80 papers presented were carefully reviewed and selected from numerous submis...
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ISBN:
(数字)9783642374012
ISBN:
(纸本)9783642374005
This book constitutes the refereed proceedings of the 15th Asia-Pacific Conference APWeb 2013 held in Sydney, Australia, in April 2013.;The 80 papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on distributed processing; graphs; Web search and Web mining; XML, RDF data and query processing; social networks; probabilistic queries; multimedia and visualization; spatial-temporal databases; data mining and knowledge discovery; privacy and security; performance, query processing and optimization. There are also sections summarizing the tutorials and containing the papers from the following workshops: second international workshop on data management for emerging network infrastructure, international workshop on soical media analytics and recommendation technologies, and international workshop on management of spatial temporal data.
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