检索结果-内蒙古大学图书馆

5th International Conference on Advancements in Computing, ICAC 2023

作者： Warnakulasuriya, Naveen De Silva, Shalinika Madushika, Janani Gamage, Sadali Jayawardena, Sanath Karunasena, Anuradha Sri Lanka Institute of Information Technology Faculty of Computing Department of Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Faculty of Computing Department of Computer Science and Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Faculty of Computing Department of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798350358131

Parkinson's disease (PD) profoundly impacts millions in Sri Lanka, emphasizing the importance of early detection for better patient outcomes. We introduce 'NeuraTrace PD,' an innovative application for early PD screening, combining brain MRI, hand-drawn image analysis, facial expression assessment, and voice analysis. For brain MRI analysis, we employed a Graph Convolutional Network (GCN), achieving an impressive accuracy of 91% and identifying distinct graph connectivity patterns using graph theory. We also use a deep Convolutional Neural Network (CNN) to reach 90% accuracy in analyzing hand-drawn images, while optimizing image resolution for efficiency and information retention. Facial expression analysis is a vital component, leveraging CNN and Constrained Local Models (CLM) to accurately extract Facial Action Units (FAUs), which contribute to a remarkable 95% accuracy using the XGBoost machine learning model. We introduce a Machine Learning (ML) algorithm and advanced signal processing to enhance voice feature analysis, offering a thorough understanding and classification of PD patients. It reaches 99% accuracy. In summary, our approach holds significant promise for advancing early PD diagnosis, ultimately improving the quality of life for those affected by this challenging condition. © 2023 IEEE.

关键词： Image resolution

来源：评论

学校读者我要写书评

暂无评论

A Sparsifier Model for Efficient Information Retrieval

A Sparsifier Model for Efficient Information Retrieval

引用

International Conference on Application of Information and Communication Technologies (AICT)

作者： Viacheslav Dobrynin Mark Sherman Roman Abramovich Alexey Platonov Faculty of Software Engineering and Computer Systems ITMO University Saint Petersburg Russian Federation

ISBN: (数字)9798350387537

ISBN: (纸本)9798350387544

The constant development of dense neural models leads to improved search quality. It is crucial to adapt these models to meet performance requirements. Solutions like SPLADE or SparseEmbed address this by solving the ranking task, whereas our work proposes addressing the simplified task of sparsifying dense vector representations. This approach facilitates the faster adaptation of new dense models for use with efficient inverted indexes. The importance of the independence property for sparse space features, achieved through the use of iVAE, is demonstrated. Additionally, the model is trained to maintain the ranking properties of the dense model, which in our case was a BERT model. As a result, the obtained model showed search quality close to the original BERT model. The proposed sparsification approach can be applied to other tasks requiring sparse spaces by adding new or replacing existing properties of the sparse space. Thus, the paper describes the main aspects of a sparsifier model applied to the task of information retrieval.

关键词： Adaptation models Information retrieval Transformers Vectors Information and communication technology Indexes

来源：评论

学校读者我要写书评

暂无评论

SAMMS: Multi-modality Deep Learning with the Foundation Model for the Prediction of Cancer Patient Survival

SAMMS: Multi-modality Deep Learning with the Foundation Mode...

引用

2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Zhu, Wen Chen, Yiwen Nie, Shanling Yang, Hai East China University of Science and Technology Department of Computer Science and Engineering Shanghai China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai China National University of Singapore Center for Continuing and Lifelong Education Singapore The University of Sydney Faculty of Engineering Australia

ISBN: (纸本)9798350337488

Cancer survival prediction is pivotal in tailoring individualized treatment strategies and guiding clinician decision-making. Yet, existing methodologies grapple with efficiently harnessing the intricate distribution of medical data spanning various modalities. In response, we present SAMMS, an advanced multi-omics multimodal deep learning framework tailored for survival prediction. SAMMS leverages the robust image segmentation model, "Segment Anything"to adeptly characterize pathological images. This prowess is further enhanced by integrating multi-omics data and clinical insights, facilitating holistic modeling across a diverse modal spectrum. The framework weaves a modality-specific subnetwork with a cross-modality common subnetwork, meticulously capturing intra-modality nuances and inter-modality correlations. SAMMS eclipsed its contemporaries by delivering remarkable performance on TCGA's LGG and KIRC tumor datasets. A battery of analyses underscored SAMMS's unparalleled capability to distill multifaceted insights from multimodal datasets, yielding richer and more integrative multimodal representations. Such strides promise significant advancements in cancer survival analytics, bolstering the precision and efficacy of patient-centric treatments, disease oversight, and clinical decision processes. © 2023 IEEE.

关键词： Multi-omics Data Pathological Images Segment Anything Survival Analysis

来源：评论

学校读者我要写书评

暂无评论

On Understanding Sports-HAR: Hierarchical, Mobile, Multi-Sensor based Classification of Table-Tennis Strokes 1

On Understanding Sports-HAR: Hierarchical, Mobile, Multi-Sen...

引用

1st International Conference of Intelligent Methods, Systems and Applications, IMSA 2023

作者： Ezzeldin, Mustafa Ghoneim, Amr S. Abdelhamid, Laila Atia, Ayman Helwan University Faculty of Computers AI Software Engineering Cairo Egypt Helwan University Faculty of Computers and AI Computer Science Cairo Egypt Helwan University Faculty of Computers and AI Information Systems Cairo Egypt Helwan Univeristy HCI-LAB Faculty of Computers and AI Computer Science Cairo Egypt Faculty of Computer Science Giza Egypt

ISBN: (纸本)9798350335569

Table Tennis is a renowned competitive and recreational sport. An Olympic sport since 1988, table tennis in-cludes several movements, shots (i.e., strokes), and positions. Consequently, many factors can affect the strokes' accuracy and strength. This paper aims twofold: to classify the type of shot and to enhance the performance of the classification by improving the recognition accuracy and reducing the computational time. To track the movement of the body parts and extract table tennis stroke information, sensors (both Accelerometers and Gyroscopes) were utilized. The extracted data are processed and passed to a P-Dollar classifier to recognize six different table tennis strokes. This work utilizes two classification approaches to evaluate the performance, both linear and hierarchical. The presented results demonstrate that the hierarchical classification yields a better accuracy of 88%, achieved in 4 seconds, while traditional linear classification achieved 83% within 6 seconds. © 2023 IEEE.

关键词： Gyroscopes

来源：评论

学校读者我要写书评

暂无评论

Success Factors of Requirement Elicitation in the Field of software engineering 4

Success Factors of Requirement Elicitation in the Field of S...

引用

4th International Conference on Advancements in Computing, ICAC 2022

作者： Attanayaka, Buddhima Nawinna, Dasuni Manathunga, Kalpani Abeygunawardhana, Pradeep K.W. Department of Computer Systems Engineering Faculty of Computing Sri Lanka Institute of Information Technology Sri Lanka Department of Computer Systems & Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Sri Lanka

ISBN: (纸本)9798350398090

Requirement elicitation (RE) is a cognitively challenging and time-consuming task in software development due to the numerous challenges associated with it including conflicting requirements, unspoken, or assumed requirements, difficulty meeting with relevant stakeholders, stakeholder resistance to change, and not enough time set aside for meetings with all stakeholders. The prime causes of software implementation failure have been identified as inadequacies in the treatment of requirements. Without collecting the quality requirement, cannot achieve the goal of a quality software product. Through identifying the success factors affecting requirement elicitation, the paths to the quality requirements can be identified. The success factors identify through this research are experience, business analyst skills, stakeholder relationship, organizational elicitation process. This study aims to identify the factors affecting requirement elicitation based on the data collected from business analysts and similar positions in the software industry through a survey, interviews, and analyzed data to provide the initial validation for the identified factors. Through the analysis, we identified the main factors affecting successful requirement elicitation with a perfect significance value of less than 0.05 for all factors. © 2022 IEEE.

关键词： Requirements engineering

来源：评论

学校读者我要写书评

暂无评论

Building the metaverse using digital twins at all scales,states,and relations

引用

Virtual Reality & Intelligent Hardware 2022年第6期4卷 459-470页

作者： Zhihan LV Shuxuan XIE Yuxi LI M.Shamim HOSSAIN Abdulmotaleb El SADDIK Department of Game Design Faculty of ArtsUppsala UniversitySweden College of Computer Science and Technology Qingdao UniversityQingdaoChina Department of Software Engineering College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia School of Electrical Engineering and Computer Science(EECS) University of OttawaOttawaOntarioCanada

Developments in new-generation information technology have enabled Digital Twins to reshape the physical world into a virtual digital space and provide technical support for constructing the *** objects can be at the micro-,meso-,or *** Metaverse is a complex collection of solid,liquid,gaseous,plasma,and other uncertain ***,the Metaverse integrates tangibles with social relations,such as interpersonal(friends,partners,and family)and social relations(ethics,morality,and law).This review introduces some principles and laws,such as broken windows theory,small-world phenomenon,survivor bias,and herd behavior,for constructing a Digital Twins model for social ***,from multiple perspectives,this article reviews mappings of tangible and intangible real-world objects to the Metaverse using the Digital Twins model.

关键词： Digital twins Metaverse Sensor

来源：评论

学校读者我要写书评

暂无评论

PMMVar: Leveraging Multi-level Protein Structures for Enhanced Coding Variant Pathogenicity Prediction

PMMVar: Leveraging Multi-level Protein Structures for Enhanc...

引用

2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Chen, Yijia Chen, Yiwen Nie, Shanling Yang, Hai East China University of Science and Technology Department of Computer Science and Engineering Shanghai China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai China National University of Singapore Center for Continuing and Lifelong Education Singapore The University of Sydney Faculty of Engineering Australia

ISBN: (纸本)9798350337488

Genomic variants, which can disrupt cellular functions, present a challenge in distinguishing deleterious from benign instances. While assessing genome-wide functional impacts, many current algorithms neglect protein tertiary structure of coding region variants due to limitations in protein structural prediction. This study introduces PMMVar, an advanced multimodal deep convolutional network, which adeptly integrates protein tertiary structures with conservation properties from ESM-2, supplemented by other protein structural sequences. PMMVar achieves outstanding performance on the latest clinical variant datasets, NCBI ClinVar (2023), and the Mendelian variant dataset, surpassing existing benchmarks. Ablation analyses validate the significance of protein multi-level structures in enhancing the model's accuracy. Overall, our findings spotlight the essential role of multi-level protein structures in pathogenicity predictions and their potential to discern deleterious genomic variants effectively. © 2023 IEEE.

关键词： deep learning multimodal pathogenicity protein structure variant

来源：评论

学校读者我要写书评

暂无评论

Evaluating the Effectiveness of the CatBoost Classifier in Distinguishing Benign Traffic, FTP BruteForce and SSH BruteForce Traffic

Evaluating the Effectiveness of the CatBoost Classifier in D...

引用

IEEE International Conference on Signal and Image Processing (ICSIP)

作者： Abdulkader Hajjouz Elena Avksentieva Faculty of Software Engineering and Computer Technology ITMO University St. Petersburg Russia

ISBN: (数字)9798350350920

ISBN: (纸本)9798350350937

In this study, we enhance information security practices by leveraging the CatBoost classifier within the challenging domain of network intrusion detection. Building upon the foundation of machine learning techniques in identifying FTP and SSH brute force attacks, our investigation introduces a refined CatBoost classifier approach by addressing the escalating sophistication of these attacks, our research meticulously analyzes the comprehensive CSE-CIC-IDS2018 and CICIDS2017 datasets. Through detailed feature selection, hyperparameter optimization, and class balancing with techniques like SMOTENC, our CatBoost model achieves high accuracy, with a rate of 99.9964% and low false alarm rate. Notably, the model demonstrates robust performance metrics, including a high F1 score over iterations, minimal loss, and a near-perfect Matthew's correlation coefficient (MCC), signifying its precision and reliability. A distinctive aspect of our study is the extensive application of SHAP (SHapley Additive exPlanations) values, providing deep insights into the model's decision-making process. These include Mean Absolute SHAP values and SHAP Value Distributions, which elucidate the significant impact and contribution of individual features to the model's predictions. Moreover, the model exhibits impressive computational efficiency, maintaining a high average processing speed of 5 million samples per second, that underscores its suitability for real-time security applications. These findings underscore the effectiveness of the CatBoost classifier in accurately identifying complex network intrusion patterns. Our investigation underscores the practical benefits of applying the CatBoost classifier in information security, contributing to the ongoing enhancement of cyber defense mechanisms with improved efficiency and interpretability.

关键词： Measurement Computational modeling Decision making Information security Network intrusion detection Predictive models Hyperparameter optimization

来源：评论

学校读者我要写书评

暂无评论

Optimization-Based Comparative System Evaluation of Single and Dual Traction Inverters with Focus on Partial Load Efficiency and Chip Area

Optimization-Based Comparative System Evaluation of Single a...

引用

2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Sachs, Christoph Stamer, Fabian Allgeier, Jan Thrimawithana, Duleepa Neuburger, Martin Esslingen University Faculty of Mobility and Technology Germany University of Stuttgart Institute for System Dynamics Germany Robert Bosch GmbH Germany The University of Auckland Dept. of Electrical Computer and Software Engineering New Zealand

ISBN: (纸本)9798350376067

The transition to electric transportation demands efficient and cost-effective powertrains. Optimizing energy use is crucial for extending range and reducing expenses. However, comparing inverter and motor efficiency based on inverter topologies is challenging due to biased methodologies that favor certain designs over others. This document introduces a novel optimization-based approach for enhancing partial load efficiency and minimizing chip area of single and dual traction inverters, indicating potential energy savings and cost reduction. Recent publications of both industry [1], [2] and academia [3] underscore the importance of these design goals achieved by either novel inverter topologies or enhanced control methods. Two promising topologies with the inherent capability of partial load optimization are evaluated regarding chip area and system efficiency to find the most suitable concept for future electric vehicle power trains. © 2024 IEEE.

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

Human Emotions Classification Using EEG via Audiovisual Stimuli and AI

引用

computers, Materials & Continua 2022年第12期73卷 5075-5089页

作者： Abdullah A Asiri Akhtar Badshah Fazal Muhammad Hassan A Alshamrani Khalil Ullah Khalaf A Alshamrani Samar Alqhtani Muhammad Irfan Hanan Talal Halawani Khlood M Mehdar Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajranSaudi Arabia Faculty of Computer Science and Engineering GIK Institute of Engineering Sciences and TechnologyTopi23460Pakistan Department of Electrical Engineering University of Engineering and TechnologyMardan23200Pakistan Department of Software Engineering University of MalakandDir LowerPakistan Department of Computer Science and Information Systems College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia Anatomy Department Medicine CollegeNajran UniversityNajranSaudi Arabia

Electroencephalogram(EEG)is a medical imaging technology that can measure the electrical activity of the scalp produced by the brain,measured and recorded chronologically the surface of the scalp from the *** recorded signals from the brain are rich with useful *** inference of this useful information is a challenging *** paper aims to process the EEG signals for the recognition of human emotions specifically happiness,anger,fear,sadness,and surprise in response to audiovisual *** EEG signals are recorded by placing neurosky mindwave headset on the subject’s scalp,in response to audiovisual stimuli for the mentioned *** a bandpass filter with a bandwidth of 1-100 Hz,recorded raw EEG signals are *** preprocessed signals then further analyzed and twelve selected features in different domains are *** Random forest(RF)and multilayer perceptron(MLP)algorithms are then used for the classification of the emotions through extracted *** proposed audiovisual stimuli based EEG emotion classification system shows an average classification accuracy of 80%and 88%usingMLP and RF classifiers respectively on hybrid features for experimental signals of different *** proposed model outperforms in terms of cost and accuracy.

关键词： Electroencephalography emotion classification signal processing multilayer perceptron random forest

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：