检索结果-内蒙古大学图书馆

2012 IEEE 6th international conference on Information and Automation for Sustainability（ICIAFS2012）

作者： Si Chen Department of Electrical Enginnering University at Buffalo the State University of New York Buffalo New York US Ling Li-na 1 Yuan Rong-chang 2 Sun Long-qing 3 1 3 China Agricultural University 2 Power Automation Department

Grade classification of seed cotton is a major problem that has an significant impact on the agricultural *** to characteristics like impurities,yellowness and brightness that extract from images of seed cotton,constructing classification model of seed cotton base on the least square *** support vector machine regression to come up with a well improved *** full learning,seed cotton classification accuracy satisfy the actual application needs.

关键词： seed cotton fuzzy math pattern recognition least square method support vector machine

来源：评论

学校读者我要写书评

暂无评论

Precoding and decoding technology based on DFE structure in field cable transmission 23

Precoding and decoding technology based on DFE structure in ...

引用

Proceedings of the 2023 6th international conference on Artificial Intelligence and pattern recognition

作者： Shuai Li Dongming Xu Anquan Zhang Xi'an University of Posts and Telecommunications China

ISBN: (纸本)9798400707674

As a digital communication technology in field cable, single-to-wire high speed digital subscriber line (***) is widely used in our country military. Due to the unsatisfactory characteristics of the field cable itself (such as signal bandwidth greater than channel bandwidth, desynchronized delay, skewed symbol, etc.) will cause intersymbol interference (ISI) problem. In this paper, a Tomlinson-Harashima precoding (th precoding) based on decision feedback equalization (DFE) structure is designed improve the signal to interference ratio and reduce the error rate of the system according to ITU-T G.991.2 protocol standard. Firstly, the tap coefficient of DFE is trained continuously according to the channel characteristics. When the training is completed, the tap coefficient in the feedback filter is sent to the precoded filter. Secondly, the feedback filter in the DFE structure is placed in the transmitter, and the feedforward filter is placed in the receiver. the simulation results show that the intersymbol interference phenomenon in the channel is obviously improved after adopting th precoding. the field programmable gate array(FPGA) simulation results show that when the th precoder works, the transmitted data waveform after delay is consistent with that after decoding. therefore, th precoding scheme realizes the function of eliminating ISI.

关键词： DFE FPGA Intersymbol Interference th Precoding Tap Coefficient

来源：评论

学校读者我要写书评

暂无评论

Improved Pathogen recognition using Non-Euclidean Distance Metrics andWeighted kNN 19

Improved Pathogen Recognition using Non-Euclidean Distance M...

引用

Proceedings of the 2019 6th international conference on Biomedical and bioinformatics Engineering

作者： Mukunthan tharmakulasingam Cihan Topal Anil Fernando Roberto La Ragione Centre for Vision Speech and Signal Processing University of Surrey United Kingdom CVSSP University of Surrey UK Eskisehir Technical University Turkey School of Veterinary Medicine University of Surrey United Kingdom

ISBN: (纸本)9781450372992

the timely identification of pathogens is vital in order to effectively control diseases and avoid antimicrobial resistance. Non-invasive point-of-care diagnostic tools are recently trending in identification of the pathogens and becoming a helpful tool especially for rural areas. Machine learning approaches have been widely applied on biological markers for predicting diseases and pathogens. However, there are few studies in the literature that have utilized volatile organic compounds (VOCs) as non-invasive biological markers to identify bacterial pathogens. Furthermore, there is no comprehensive study investigating the effect of different distance and similarity metrics for pathogen classification based on VOC data. In this study, we compared various non-Euclidean distance and similarity metrics with Euclidean metric to identify significantly contributing VOCs to predict pathogens. In addition, we also utilized backward feature elimination (BFE) method to accurately select the best set of features. the dataset we utilized for experiments was composed from the publications published between 1977 and 2016, and consisted of associations in between 703 VOCs and 11 *** performed extensive set of experiments with five different distance metrics in both uniform and weighted manner. Comprehensive experiments showed that it is possible to correctly predict pathogens by using 68 VOCs among 703 with 78.6% accuracy using k-nearest neighbour classifier and Sorensen distance metric.

关键词： pathogen detection bioinformatics feature selection Distance metrics machine learning backward feature elimination (BFE)

来源：评论

学校读者我要写书评

暂无评论

Attack-Aware Capability Assessment Method Based on Specific Semantic Search

Attack-Aware Capability Assessment Method Based on Specific ...

引用

international conference on Electronic Engineering and Informatics (EEI)

作者： Daojuan Zhang Qi Zhao Yuman Wang Shu Li Zheng Tian Yizhen Sun State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute co. Ltd Beijing China Hunan Provincial Key Laboratory of Internet of Things in Electricity State Grid information & Communication Company of Hunan Electric Power Corporation Changsha China

ISBN: (数字)9798350353594

ISBN: (纸本)9798350353600

In this paper, we propose an attack perception capability assessment method based on the specific semantic search for the problem of attack perception capability assessment of security protection equipment for power monitoring systems. the method aims to improve the recognition and localization accuracy of common attacks by accurately correlating the output products of security equipment with the execution of attack test cases. the research employs an attack-specific semantic generation technique that combines attack attribute values with timestamps to form specific semantics for subsequent matching. pattern matching algorithm, specifically the BM (Boyer-Moore) algorithm, is further utilized to match the specific semantics with the output products of the security device Snort to achieve attack localization. Experimental results demonstrate that Snort exhibits high accuracy in perceiving the majority of attack types and exhibits an enhanced perception rate compared to certain baseline methods. In summary, the method proposed in this paper effectively improves the sensing ability of security equipment to attacks on the power monitoring system and provides a new idea for the performance evaluation of security protection equipment.

关键词： Location awareness Performance evaluation Accuracy Semantic search Sensors Security Protection Informatics Monitoring pattern matching

来源：评论

学校读者我要写书评

暂无评论

Credit Card Fraud Detection Using Symbolic Aggregate Approximation

Credit Card Fraud Detection Using Symbolic Aggregate Approxi...

引用

Blockchain Computing and Applications (BCCA), international conference on

作者： Snit D. Zerea Belsabel T. Woldemichael Feven B. Araya Richard A. Ikuesan College of Technological Innovation Zayed University Abu Dhabi UAE

ISBN: (数字)9798350351538

ISBN: (纸本)9798350351545

In the current digital age, credit card fraud is a cybercrime that costs billions of dollars every year through fraudulent transactions. this study aims to identify fraudulent credit card transactions using Symbolic Aggregate Approximation (SAX) and anomaly discovery through motifs and discords. To do this, credit card data is used as time series data and then divided into equal-length segments. Each segment is then converted into a symbolic representation using a pre-defined threshold. A web-based interface is further developed to load a collection of credit card transaction data, based on the proposed SAX method. the preliminary results show that the proposed approach is capable of identifying fraudulent transactions within a set of transactions. By integrating this approach with other fraud detection mechanisms, a near real-time fraud detection process can be developed. this approach therefore provides a potential for context-independent fraud detection which is a major challenge in the fraud detection domain.

关键词： Machine learning algorithms Costs Aggregates Time series analysis Credit cards Information age Real-time systems Fraud pattern recognition Security

来源：评论

学校读者我要写书评

暂无评论

Moving Forward Together: A Multi-User pattern Extraction Neural Model for Sequential Recommendations 23

Moving Forward Together: A Multi-User Pattern Extraction Neu...

引用

Proceedings of the 2023 6th international conference on Artificial Intelligence and pattern recognition

作者： Xiangpeng Du Xiaoge Li Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xian University of Posts and Telecommunications China

ISBN: (纸本)9798400707674

the sequential recommendation is a very important task in recommendation systems. the aim of it is to dynamic predict user's interests based on their historical behaviors. Despite recent progress, most of deep learning approaches focus on extracting the behavioral patterns of a single user. Pulling multiple users can increase the diversity of historical information. In this paper, we propose multi-user behavioral pattern extraction model (TMGN) via a combination of traditional behavioral pattern extraction and graph convolutional aggregation. Concretely, TMGN first learns the graph structure of users and items. then it performs graph convolution aggregation to derive a representation of users to extract user interest features. We recall the users with the highest similarity by calculating the cosine similarity of each candidate user. Finally, we inject multiple users' sequence patterns and time information into the muti-head attention mechanism. Experiments on actual data (Movielens1m, Movielen20m and Amazon beauty) show that the proposed method outperforms current state-of-the-art sequential recommendation methods. TMGN achieves an average improvement of 5.67%, 5.75%, 7.32%, and 7.19% over the most robust baseline in Hit@5, Hit@10, NDCG@5, and NDCG@10, respectively. We provide extensive ablation studies to analyze the impact of each model component on TMGN.

关键词： Graph Convolutional Network Self-attention Sequential Recommendation Sequential prediction Temporal Embedding

来源：评论

学校读者我要写书评

暂无评论

Emotion-Based Media Recommendation System

Emotion-Based Media Recommendation System

引用

Cybernetics, Cognition and Machine Learning Applications (ICCCMLA), IEEE international conference on

作者： Sayon Chakraborty Shubham Shreya Singh Mandeep Kaur Nitin Rakesh Monali Gulhane Department of Computer Science & Engineering SET Sharda University India Department of CSE Symbiosis Institute of Technology Nagpur Campus Symbiosis International (Deemed University) Pune Nagpur India

ISBN: (数字)9798331505790

ISBN: (纸本)9798331505806

Emotion is a state of physical arousal that is subjective and private to the individual. Human emotions are divided into fear, anger, surprise, sadness, happiness, etc. this emotional umbrella encompasses a wide range of other emotions, including joy and contempt; they are subtle emotions. When it comes to recognizing emotions and present mental states, facial expressions are crucial (i.e., emotional and spiritual). Detecting these emotions can be difficult at times, as even minor variances might result in distinct displays. To detect emotions and produce good results, neural networks and machine learning were applied. Machine learning algorithms have proven to be very useful in pattern recognition and classification and thus can also be used for mood detection. With the development of digital music technology, it is also necessary to develop a personalized music recommendation system to recommend music to users. Emotions are an essential part of the human psyche. It has many different types, and the main purpose of our proposed system is to distinguish them. For this, our proposed system is based on the proposed structure of video content that is related to human emotions. Recommendation system based on user logs or history. the recommendation technique we use is not fully personalized nor is it considered a point of user content. therefore, the solution to this problem is to recommend personalized content based on emotional characteristics. According to letter of our proposed system, taking into account aspects such as age, gender and emotional characteristics, our main motivation is to control the problem of accuracy in applications running. Our proposed emotion-based media recommendation system is a novel and innovative approach that has the potential to revolutionize the way we interact with digital media.

关键词： Emotion recognition Portable computers Webcams Face recognition Personal voice assistants Nose Machine learning Media Feature extraction Recommender systems

来源：评论

学校读者我要写书评

暂无评论

Research on the pattern recognition Method of Slurry Pipeline Safety Status

Research on the Pattern Recognition Method of Slurry Pipelin...

引用

2016 6th international conference on Machinery,Materials,Environment,Biotechnology and Computer(MMEBC 2016)

作者： Chengjiang Zhou Jiande Wu Jingzong Yang Faculty of Information Engineering and Automation Kunming University of Science and Technology Engineering Research Center for Mineral Pipeline Transportation of Yunnan Province

For the non-linear relationships of main influence factors of slurry pipeline safety status and the confusable problem of slurry pipeline safety status, this paper used the cross validation method to select the optimum parameters of the kernel function and combined the support vector machine to diagnose the security status of slurry pipelineFirst standardize the test data that affect the slurry pipeline safety statusthen according to the accuracy of fault diagnosis and used cross validation method to optimize the kernel functions parametersAnd as the parameters of support vector machine(SVM) to identify the slurry pipeline safety statusthrough the analytic results of the normal state of slurry pipeline, high pressure diaphragm pumps wear and pipeline blockage show that using cross validation method to improve kernel function parameters of support vector machine(SVM) model can accurately identify pulp pipeline safety state and fault type.

关键词： Slurry pipeline support vector machine fault diagnosis

来源：评论

学校读者我要写书评

暂无评论

A transferable model for pedestrian intention prediction in crosswalks based on mobile phone sensors 22

A transferable model for pedestrian intention prediction in ...

引用

Proceedings of the 2022 6th international conference on Electronic Information Technology and Computer Engineering

作者： Xinyu Wang Xikai Wang Sijing Guo School of Automotive Engineering Wuhan University of Technology China

ISBN: (纸本)9781450397148

To accommodate the path planning of autonomous vehicle (AV), many researchers utilize on-board sensors to predict pedestrians’ intention, but the on-board sensors cannot detect occluded pedestrians. Roadside sensors can solve this problem, but with a high cost if deployed at every crosswalk. Hence, this paper aims at utilizing mobile phone sensors to predict the pedestrians’ intentions at crosswalks. A transferable prediction model is built in the paper, with a purpose of saving the expense of hardware and data collection. that is, the model trained by the pedestrians’ data at one crosswalk can provide high accuracy at other crosswalks, via extracting the features associating the geometric structure of the crosswalks and the pedestrians’ motion data. Various algorithms were applied to build the prediction model, and results showed that the prediction accuracy exceeds 90% in non-transfer task, 80% in normal transfer tasks, with a distance of 5 meters ahead of crossing.

关键词： Mobile phone Pedestrian protection Machine learning pattern recognition V2X Pedestrian intention prediction

来源：评论

学校读者我要写书评

暂无评论

Augmented cell-graphs for automated cancer diagnosis

引用

bioinformatics 2005年第Sup2期21卷 7-12页

作者： Demir, C Gultekin, SH Yener, B Rensselaer Polytech Inst Dept Comp Sci Troy NY 12180 USA CUNY Mt Sinai Sch Med Dept Pathol New York NY 10029 USA

this work reports a novel computational method based on augmented cell-graphs (ACG), which are constructed from low-magnification tissue images for the mathematical diagnosis of brain cancer (malignant glioma). An ACG is a simple, undirected, weighted and complete graph in which a node represents a cell cluster and an edge between a pair of nodes defines a binary relationship between them. Both the nodes and the edges of an ACG are assigned weights to capture more information about the topology of the tissue. In this work, the experiments are conducted on a dataset that is comprised of 646 human brain biopsy samples from 60 different patients. It is shown that the ACG approach yields sensitivity of 97.53% and specificities of 93.33 and 98.15% (for the inflamed and healthy, respectively) at the tissue level in glioma diagnosis.

关键词： Algorithms Artificial Intelligence Brain Neoplasms/pathology Glioma/pathology Humans Image Interpretation, Computer-Assisted/methods pattern recognition, Automated/methods Reproducibility of Results Sensitivity and Specificity

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：