The two volume set LNCS 5506 and LNCS 5507 constitutes the thoroughly refereed post-conference proceedings of the 15th International Conference on Neural Information Processing, ICONIP 2008, held in Auckland, New Zeal...
详细信息
ISBN:
(数字)9783642030406
ISBN:
(纸本)9783642030390
The two volume set LNCS 5506 and LNCS 5507 constitutes the thoroughly refereed post-conference proceedings of the 15th International Conference on Neural Information Processing, ICONIP 2008, held in Auckland, New Zealand, in November 2008. The 260 revised full papers presented were carefully reviewed and selected from numerous ordinary paper submissions and 15 special organized sessions. 116 papers are published in the first volume and 112 in the second volume. The contributions deal with topics in the areas of data mining methods for cybersecurity, computational models and their applications to machine learning and pattern recognition, lifelong incremental learning for intelligent systems, application of intelligent methods in ecological informatics, pattern recognition from real-world information by svm and other sophisticated techniques, dynamics of neural networks, recent advances in brain-inspired technologies for robotics, neural information processing in cooperative multi-robot systems.
Welcome to the proceedings of APPT 2005: the 6th International Workshop on Advanced Parallel Processing Technologies. APPT is a biennial workshop on parallel and distributed processing. Its scope covers all aspects of...
详细信息
ISBN:
(数字)9783540321071
ISBN:
(纸本)9783540296393
Welcome to the proceedings of APPT 2005: the 6th International Workshop on Advanced Parallel Processing Technologies. APPT is a biennial workshop on parallel and distributed processing. Its scope covers all aspects of parallel and distributed computing technologies, including architectures, software systems and tools, algorithms, and applications. APPT originated from collaborations by researchers from China and Germany and has evolved to be an international workshop. APPT 2005 was the sixth in the series. The past ?ve workshops were held in Beijing, Koblenz, Changsha, Ilmenau, and Xiamen, respectively. The Program Committee is pleased to present the proceedings for APPT 2005. This year, APPT 2005 received over 220 submissions from researchers all over the world. All the papers were peer reviewed by two to three Program Committee members on their relevance, originality, signi?cance, technical qu- ity, and presentation. Based on the review result, 55 high-quality papers were selected to be included in the proceedings. The papers in this volume represent the forefront of research on parallel processing and related ?elds by researchers from China, Germany, USA, Korea, India, and other countries. The papers - cepted cover a wide range of exciting topics, including architectures, software, networking, and applications.
Recently, the booming growth of patent applications has brought an unprecedented challenge in performing efficient intellectual property management. Therefore, intelligent approaches are urgently needed to analyze int...
详细信息
Recently, the booming growth of patent applications has brought an unprecedented challenge in performing efficient intellectual property management. Therefore, intelligent approaches are urgently needed to analyze intrinsic patterns of patents. However, a long-standing obstacle is the lack of effective methods for modeling the dynamic and diverse examination process of patent applications, which can benefit a wide range of downstream tasks for patent management. In fact, the major challenges lie in how to discover and integrate domain-specific properties from large-scale unlabeled examination data. To this end, in this paper, we propose a Self-supervised Examination Process Modeling (SEPM) framework to learn the contextualized embedding for patents through modeling their examination processes. Specifically, we first design a multi-aspect event embedding layer, which leverages the fine-tuned language model, frequent-pattern embedding, and time encoding to capture the semantic, frequent-pattern and temporal information of examination events, respectively. Then, a mutual-information-aware integration layer is applied to fuse the extracted features into multi-aspect embedding considering their mutual interactions. Further, we develop a multi-objective sequential neural network for learning the contextualized patent representation, which is achieved through jointly learning two self-supervised objectives, namely event code and event lag auto-regression. To explore the application potential of SEPM, we fine-tune the well-trained model for three important downstream tasks of patent management, including the prediction of next events, patent classification, and grant prediction. In the end, extensive experiments with real-world data from the US Patent and Trademark Office verify the effectiveness and application prospects of the proposed framework.
The recent breakthrough in wireless power transfer technology enables power to be delivered between transceivers, which is quite helpful for sensor-cloud systems. Traditional charging schemes are only suitable for sta...
详细信息
The recent breakthrough in wireless power transfer technology enables power to be delivered between transceivers, which is quite helpful for sensor-cloud systems. Traditional charging schemes are only suitable for static sensors, while the issue of charging mobile sensors is ignored. In this paper, we make the first attempt to serve mobile sensors in the sensor-cloud systems in a “chasing” way, where a mobile charger can chase mobile sensors to replenish them. We formalize the charging utility MAximization Problem for dynamic sensors with a mobile charger (MAP) and propose a ChaseCharge algorithm based on RNN to solve it. Theoretical analyses are presented to explore the features of the proposed scheme. We carry out simulations, and the results show that the performance of our algorithm outperforms comparison algorithms by 33% in utility on average. Test-bed experiments are conducted to validate the applicability of the proposed scheme in oceanic monitoring applications.
In this paper, a uniform calculus-based approach for synthesizing monitors checking correctness properties specified by a large variety of logics at runtime is provided, including future and past time logics, interval...
详细信息
暂无评论