检索结果-内蒙古大学图书馆

arXiv 2018年

作者： Stephenson, Matthew Renz, Jochen Ge, Xiaoyu Department of Data Science and Knowledge Engineering Maastricht University Maastricht Netherlands Research School of Computer Science Australian National University Canberra Australia

The physics-based simulation game Angry Birds has been heavily researched by the AI community over the past five years, and has been the subject of a popular AI competition that is currently held annually as part of a leading AI conference. Developing intelligent agents that can play this game effectively has been an incredibly complex and challenging problem for traditional AI techniques to solve, even though the game is simple enough that any human player could learn and master it within a short time. In this paper we analyse how hard the problem really is, presenting several proofs for the computational complexity of Angry Birds. By using a combination of several gadgets within this game’s environment, we are able to demonstrate that the decision problem of solving general levels for different versions of Angry Birds is either NP-hard, PSPACE-hard, PSPACE-complete or EXPTIME-hard. Proof of NP-hardness is by reduction from 3-SAT, whilst proof of PSPACE-hardness is by reduction from True Quantified Boolean Formula (TQBF). Proof of EXPTIME-hardness is by reduction from G2, a known EXPTIME-complete problem similar to that used for many previous games such as Chess, Go and Checkers. To the best of our knowledge, this is the first time that a single-player game has been proven EXPTIME-hard. This is achieved by using stochastic game engine dynamics to effectively model the real world, or in our case the physics simulator, as the opponent against which we are playing. These proofs can also be extended to other physics-based games with similar mechanics. Copyright © 2018, The Authors. All rights reserved.

关键词： Computational complexity

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of Robust Multicast Trees for Lossy Wireless Ad-Hoc Networks 15

Design and Implementation of Robust Multicast Trees for Loss...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Preetha, M. Sohal, Jagmeet Sampangi Rama Reddy, B.R. Sharma, Nakul S. Hemelatha, S. Singh, Manpreet Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai127 India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh 174103 India School of Sciences Department of Physics & Electronics Karnataka Bangalore India Vishwakarma Institute of Technology Department of Artificial Intelligence & Data Science Pune India Karpagam Academy of Higher Education Department of Computer Science Engineering Coimbatore641021 India Chitkara University Institute of Engineering and Technology Chitkara University Centre for Interdisciplinary Research for Business and Technology Punjab India

ISBN: (纸本)9798350370249

This paper affords a layout and implementation of a sturdy multicast tree technique for loss wireless advert-hoc networks. The proposed technique seeks to provide dependable delivery of statistics in dynamic environments where hyperlinks revel in excessive degrees of packet loss. This method is based on a mixture of spanning tree clustering, hyperlink-country routing, and acknowledgements-primarily based recuperation mechanisms, using re-transmissions and adaptive retransmission periods to catch up on packet loss. The usage of these combined techniques permits for minimal deterioration of verbal exchange performance because of packet losses, whilst retaining a green network layout. Simulations had been conducted to evaluate the overall performance of the proposed method in assessment to previous works. The effects showed that the proposed method outperformed the other techniques in terms of multicast message transport fee. The proposed approach is also proven to reduce overhead site visitors because of retransmissions while as compared to previous works. The proposed method affords a suitable and efficient solution for reliable multicasting in loss wireless ad-hoc networks. © 2024 IEEE.

关键词： Adaptive Affords Compared Conducted Periods Previous Retransmission Transport

来源：评论

学校读者我要写书评

暂无评论

Enhanced Route Optimization: Incorporating Road Safety Factors for Optimal Path Selection 4

Enhanced Route Optimization: Incorporating Road Safety Facto...

引用

4th International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2024

作者： Subash, R. Prathaban, Banu Priya Ganeshkumar, N. Gopinathan, S. Srm Institute of Science and Technology School of Computing Department of Computing Technologies Chennai India Srm Institute of Science and Technology School of Computing Department of Networking and Communications Chennai India Gitam School of Technology Gandhi Institute of Technology and Management Department of Computer Science and Engineering Karnataka Bengaluru562163 India Sri Sai Ram Institute of Technology Department of Artificial Intelligence and Data Science Chennai India

ISBN: (纸本)9798331508845

Efficient route optimization is a crucial concern in modern transportation systems, influencing travel time, resource consumption, and user satisfaction. By empowering users to select their priority parameters, such as safety or efficiency, this project enables travellers to make eco-conscious choices and select routes that minimize their environmental footprint. Real-time data integration ensures users can bypass traffic jams and accidents, reducing emissions and fuel consumption. Furthermore, the focus on safety factors helps prevent accidents, thereby fostering safer road environments. Existing systems often fall short, providing limited customization and overlooking safety and sustainability priorities. To bridge these gaps, this project introduces an advanced route planning system that empowers users to select their priority parameters, integrates real-time data for up-to- the-minute updates, and prioritizes road safety. It introduces a pioneering approach that enhances the Dijkstra Algorithm by integrating real-time accident rate and travel time data into the route optimization process. By considering these additional factors, the algorithm produces routes that not only minimize distance but also prioritize safety and time efficiency in dynamic real-world conditions. The algorithm's multi-factor optimization considers distance, accident rates, and travel times, enabling the creation of routes that balance these criteria and offer improved decision-making for users through a user- friendly interface. The algorithm's dynamic adaptability, multi- factor optimization, and practical implementation showcase its potential to revolutionize how routes are planned, leading to safer, faster, and more informed travel experiences. © 2024 IEEE.

关键词： Travel time

来源：评论

学校读者我要写书评

暂无评论

Asynchronous P systems for SAT and Hamiltonian cycle problem

Asynchronous P systems for SAT and Hamiltonian cycle problem

引用

World Congress on Nature & Biologically Inspired Computing (NaBIC)

作者： Kota Ishii Akihiro Fujiwara Hirofumi Tagawa Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka Japan NTT Data Corporation Limited Toyosu Tokyo Japan

In the present paper, we consider the asynchronous parallelism in membrane computing, and propose fully asynchronous P systems such that any number of applicable rules may be applied in one step. Since there is no restrictive assumption for application of rules, sequential and maximal parallel executions are allowed on the asynchronous P system. We propose two asynchronous P systems for the satisfiability (SAT) and Hamiltonian cycle problem. We first propose an asynchronous P system that solves SAT with n variables and m clauses, and show that the proposed P system computes SAT in O(mn2 n ) sequential steps or O(mn) parallel steps using O(mn) kinds of objects. We next propose an asynchronous P system that solves the Hamiltonian cycle problem with n nodes, and show that the proposed P system computes the problem in O(n!) sequential steps or O(n 2 ) parallel steps using O(n 2 ) kinds of objects.

关键词： Biomembranes Tin Read only memory

来源：评论

学校读者我要写书评

暂无评论

Quantum-Improved Weather Forecasting: Integrating Quantum Machine Learning for Precise Prediction and Disaster Mitigation

Quantum-Improved Weather Forecasting: Integrating Quantum Ma...

引用

Quantum Technologies, Communications, Computing, Hardware and Embedded Systems Security (iQ-CCHESS), International Conference on

作者： S Suhas S Divya School of Computer Science and Engineering Vellore Institute of Technology Chennai India Centre for Advanced Data Science Vellore Institute of Technology Chennai India

In numerous industries, weather forecasting is essential for making informed decisions and mitigating the effects of extreme weather events. The complexity and chaos of weather systems, however, place restrictions on standard procedures, leading to errors and significant threats. We suggest the Quantum Improved Weather Forecast framework, which combines quantum machine learning methods with conventional methodologies, to solve these issues. By using quantum algorithms including quantum support vector machines, quantum neural networks, and quantum clustering, the QWF framework seeks to improve accuracy. Despite a few drawbacks, the QWF framework provides a method to revolutionize weather forecasting by enhancing prediction accuracy and facilitating improved catastrophe preparedness. It may prevent fatalities, safeguard critical infrastructure, and promote sustainable growth.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Intervention of resource allocation strategies on spatial spread of epidemic

Research Square

引用

Research Square 2021年

作者： Zhang, Kebo Han, Yuexing Gou, Min Wang, Bing School of Computer Engineering and Science Shanghai University Shanghai China Shanghai Institute for Advanced Communication and Data Science Shanghai University Shanghai China

Medical resources are crucial in mitigating the epidemic, especially during pandemics such as the ongoing COVID-19. Thereby, reasonable resource deployment inevitably plays a significant role in suppressing the epidemic under limited resources. When an epidemic breaks out, people can produce resources for self-protection, or donate resources to help others. That is, the exchange of resources also affects the transmission between individuals, thus, altering the epidemic dynamics. To understand factors on resource deployment and the interplay between resource and transmission we construct a metapopulation network model with resource allocation. Our results indicate actively or promptly donating resources is not helpful to suppress the epidemic under both homogeneous population distribution (HOD) and heterogeneous population distribution (HED). Besides, strengthening the speed of resource production can significantly increase the recovery rate so that reduce the final outbreak size. These results may provide policy guidance towards epidemic containment. © 2021, CC BY.

关键词： Resource allocation

来源：评论

学校读者我要写书评

暂无评论

A New Method of Named Entity Recognition on Biology Domain

A New Method of Named Entity Recognition on Biology Domain

引用

International Conference on Intelligent Computation Technology and Automation, ICICTA

作者： Wande Zhuang Chengfan Li Qingjie Zhang Xuehai Ding Junjuan Zhao School of Computer Engineering and Science Shanghai University Shanghai China Shanghai Institute of Advanced Communication and Data Science Shanghai University Shanghai China

It is the phenotypic data of microbial taxonomy that is of great significance. It can be used not only for the identification of microbial taxonomy but also for the study of the interaction between human and the environment. There are bilstm-CRF, Bert-CRF and other models are commonly used for named entity recognition (NER) recently. However, these methods do not consider the sequence information of neurons and do not analyze the hierarchical structure of sentences. In the field of biological phenotypes, there are longer sentences and complex words, the named entity recognition with neural network performs not very well. Based on this, this paper proposed a new NER method which is named BERT-ON-LSTM to identify and extract microbial phenotypic entities from the literature. This paper improved the Bidirectional Encoder Representations from Transformers (Bert) which enabled the model to learn the hierarchical structure information and be more sensitive to words that require long-term memory. And then, conditional random field (CRF) is used to decode since it can be calculated the joint probability distribution of the whole tag sequence. The experimental results on three data sets prove that our model is effective.

关键词： Biological system modeling Neurons Taxonomy Memory management Transformers data models Probability distribution

来源：评论

学校读者我要写书评

暂无评论

PhishZip: A New Compression-based Algorithm for Detecting Phishing Websites

PhishZip: A New Compression-based Algorithm for Detecting Ph...

引用

IEEE Conference on Communications and Network Security (CNS)

作者： Rizka Purwanto Arindam Pal Alan Blair Sanjay Jha School of Computer Science and Engineering University of New South Wales Australia Data61 CSIRO Sydney New South Wales Australia

ISBN: (数字)9781728147604

ISBN: (纸本)9781728147611

Phishing has grown significantly in the past few years and is predicted to further increase in the future. The dynamics of phishing introduce challenges in implementing a robust phishing detection system and selecting features which can represent phishing despite the change of attack. In this study, we propose PhishZip which is a novel phishing detection approach using a compression algorithm to perform website classification and demonstrate a systematic way to construct the word dictionaries for the compression models using word occurrence likelihood analysis. PhishZip outperforms the use of best-performing HTML-based features in past studies, with a true positive rate of 80.04%. We also propose the use of compression ratio as a novel machine learning feature which significantly improves machine learning based phishing detection over previous studies. Using compression ratios as additional features, the true positive rate significantly improves by 30.3% (from 51.47% to 81.77%), while the accuracy increases by 11.84% (from 71.20% to 83.04%).

关键词： Phishing Dictionaries Feature extraction Compression algorithms Machine learning Machine learning algorithms

来源：评论

学校读者我要写书评

暂无评论

Prediction of Suicidal Behaviour among the users on Social Media using NLP and ML

Prediction of Suicidal Behaviour among the users on Social M...

引用

Emerging Systems and Intelligent Computing (ESIC), International Conference on

作者： Tapas Kumar Mishra G. Sucharitha Narala Siddhartha Bommena Raju Sachi Nandan Mohanty Dept of Computer Science and Engineering SRM University-Ap Andhra Pradesh India Dept of Electronics and Communication Engineering Institute of Aeronautical Engineering Telangana India Dept of Computer Science and Engineering(Data Science) Institute of Aeronautical Engineering Telangana India School of Computer Science and Engineering VIT-AP University Amaravati Andhra Pradesh India

suicide attempts. Our findings contribute to the growing field of suicide prevention through cutting-edge machine learning techniques applied to natural language data. According to our experimental results, the PM model outperformed other machine learning algorithms with the highest classification score. It achieved an impressive accuracy of 92% and an F1 score of 85%. These findings highlight the effectiveness and potential of the PM model for the task at hand. Suicides are happening more often these days. Social media messages and chats are the preferred means of expression for those who are committing suicide. Several studies have shown that it is possible to spot suicide suspects from their online conversations and posts on social media. Consequently, it is imperative to create a machine learning system for automatic early identification of suicide ideation or any abrupt changes in a user’s behaviour by examining his or her posts and chats on social media such as Twitter, Instagram, WhatsApp, and Facebook. Our research is focused on significantly improving the performance of our model to accurately recognize early indications of suicide attempts with high precision, thus contributing to the prevention of such tragic events. To achieve this, we utilized advanced text pre-processing techniques and feature extraction approaches, including CountVectorizer and word embedding. Our study involved training both XGBoost and NLP models, which were rigorously evaluated using a substantial dataset of 34,100 samples. Furthermore, to assess real-world applicability, we conducted live tests of our model using tweets collected via the Stream lit python-based web interface tool. The results of our experiments are promising, demonstrating the potential of our approach in detecting early signs of distress and aiding in the timely intervention to prevent.

关键词：

来源：评论

学校读者我要写书评

暂无评论

DCSim: Computing and Networking Integration based Container Scheduling Simulator for data Centers

arXiv

引用

arXiv 2024年

作者： Hu, Jinlong Rao, Zhizhe Liu, Xingchen Deng, Lihao Dong, Shoubin Guangdong Key Lab of Multimodal Big Data Intelligent Analysis School of Computer Science and Engineering South China University of Technology Guangzhou China

The increasing prevalence of cloud-native technologies, particularly containers, has led to the widespread adoption of containerized deployments in data centers. The advancement of deep neural network models has increased the demand for container-based distributed model training and inference, where frequent data transmission among nodes has emerged as a significant performance bottleneck. However, traditional container scheduling simulators often overlook the influence of network modeling on the efficiency of container scheduling, primarily concentrating on modeling computational resources. In this paper, we focus on a container scheduling simulator based on collaboration between computing and networking within data centers. We propose a new container scheduling simulator for data centers, named DCSim. The simulator consists of several modules: a data center module, a network simulation module, a container scheduling module, a discrete event-driven module, and a data collection and analysis module. Together, these modules provide heterogeneous computing power modeling and dynamic network simulation capabilities. We design a discrete event model using SimPy to represent various aspects of container processing, including container requests, scheduling, execution, pauses, communication, migration, and termination within data centers. Among these, lightweight virtualization technology based on Mininet is employed to construct a software-defined network. An experimental environment for container scheduling simulation was established, and functional and performance tests were conducted on the simulator to validate its scheduling simulation capabilities. Copyright © 2024, The Authors. All rights reserved.

关键词： Software testing

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：