检索结果-内蒙古大学图书馆

Intelligent Cybernetics Technology & Applications (ICICyTA), International Conference on

作者： Michael S. M. Pakpahan Lukito Edi Nugroho Widyawan Widyawan Ajie Kusuma Wardhana Muhammad Ardian R.A Rangga Satria Astagenta Dept. of Electrical and Information Engineering Universitas Gadjah Mada Yogyakarta Indonesia Dept. Informatics Faculty of Computer Science Universitas AMIKOM Yogyakarta Yogyakarta Indonesia

Addressing its growing number and vital role, decentralization of cloud computing becoming a necessity. Fog computing aims to bring application closer to the data source-typically at the network’s edge by leveraging local resources to provide faster data processing and decision-making. Fog computing then has to place application strategically to use its limited fog resource to improve application performance metrics. This problem known as Fog Application Placement Problem (FAPP) has been approached using previous methods that rely on rules and prior knowledge that may not be adaptive, but rather being overly specialized to specific problems. Deep learning with its learning mechanism, can offer more adaptable and dynamic solutions for a wide range of scenarios, especially in fog network that continuously evolve. This research investigate Seq2seq placement model inherent limitations, notably the impracticality of generating every possible pattern from all potential request configurations. We aim to address and answer the following critical questions: 1) How does the model’s performance vary when confronted with unseen requests or an augmented number of modules, especially considering the limitations in training data?; 2) Can the seq2seq model, even with its training limitations, adhere to the heuristic rules of the dataset when dealing with unfamiliar problems? This research shows that in similar availability, there is a reduction of almost half of the response time with 183.03 ms, 2.93 number of hops, and 0.87 megabyte of transmitted messages against the hop3 algorithm. Moreover, we highlight the ability of seq2seq model to follow heuristic rules in unseen scenarios.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Pose-free visual servoing from 3D measurements

Pose-free visual servoing from 3D measurements

引用

European Control Conference (ECC)

作者： Adrian Burlacu Radu L. Rosca Andrei I. Iancu Enric Cervera Dept. of Automatic Control and Applied Informatics Gheorghe Asachi Technical University of Iasi Romania Dept. of Computer Science and Engineering Jaume I University Spain

In this paper, a novel approach to visual servo control robotic systems is proposed. It is focused on developing a solution using 3D point features without recovering the rigid object’s pose. Pose-free motion is achieved using motion parameterization techniques based on dual numbers and dual vectors. Considering an imposed velocity field over the motion of the 3D point features ensemble, this work proposes a close-form solution to a visual servoing problem. The solution provides stable motion control while preserving the image features in the field of view. However, when some point features leave the field of view, their contribution to the control law is dropped without losing stability. The proposed solution is easy to tune and implement. Various scenarios are used in simulations and real experiments to show how the proposed solution overcomes classic servoing problems.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Alzheimer's Disease Classification Using Genetic Data

Alzheimer's Disease Classification Using Genetic Data

引用

2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

作者： Khanal, Subash Chen, Jin Jacobs, Nathan Lin, Ai-Ling University of Kentucky Dept. of Computer Science LexingtonKY United States Inst. for Biomedical Informatics University of Kentucky LexingtonKY United States University of Missouri Dept. of Radiology ColumbiaMO United States

ISBN: (纸本)9781665401265

There has been a recent surge of interest in using genetic data to build ML-based accurate and interpretable disease classification models. In this line of research, we separately assess the potential of the peripheral blood gene expression data as well as the Single Nucleotide Polymorphism (SNP) data in building ML models for AD classification. We present a systematic approach on feature selection and ML model design using both types of genetic data provided by the Alzheimer's Disease Neuroimaging Initiatives (ADNI). Our two-step feature selection produced a curated list of important genes. In addition to these selected genetic features, to examine the role of non-genetic covariates, we included age and number of education years (EDU) as extra features. In the Control (CN) vs. AD classification, the best performing classifier, XGBoost, trained with gene expression features only and that with extra features included had Area Under Curve (AUC) of 0.64 and 0.65 respectively. However, AUC for the same task using SNP data only and that with extra features included was 0.56 and 0.64 respectively. The just above chance results of classifier trained with SNP features and the improvement when used along with additional covariates indicate low potential of SNP data in AD classification when used alone while also indicating the importance of non-genetic factors associated with AD. Nevertheless, with well above chance performance, gene expression features show great potential especially between groups of AD progression, i.e., CN vs. AD, CN vs. EMCI, EMCI vs. AD and LMCI vs. AD. The source code and manual are available at https://***/mvrl/ADNI_Genetics. © 2021 IEEE.

关键词： Feature Selection

来源：评论

学校读者我要写书评

暂无评论

Smart Homes Under Siege: Assessing the Robustness of Physical Security Against Cyber Attackers

SSRN

引用

SSRN 2023年

作者： Allen, Ashley Mylonas, Alexios Vidalis, Stilianos Gritzalis, Dimitris Cybersecurity and Computing Systems Research Group Dept. of Computer Science University of Hertfordshire United Kingdom Dept. of Informatics Athens University of Economics & Business Greece

Nowadays domestic smart security devices, such as smart locks, smart doorbells, and security cameras, are becoming increasingly popular with users, due to ease of use, convenience, and declining prices. Unlike conventional user security devices, such as alarms and locks, current standards, such as the British TS 621, are not easily understandable by end users due to the technical language employed. Users also have very few sources of unbiased information regarding product performance in real world conditions and protection against attacks and, as a result, tend to take manufacturer claims at face value. This means that, as this work proves, their users may be exposed to threats, such as theft, impersonation (should an attacker steal their credentials), and even physical injury, if the device fails and is used to prevent access to hazardous environments. As such, this paper deploys several attacks using popular wireless attack vectors (i.e., 433MHz radio, Bluetooth, and RFID) against domestic smart security devices to assess the protection offered against cyber attackers-burglars. Our results suggest that users are open to considerable cyber physical attacks, irrespective if they use generic (i.e., no name) or branded smart security devices, due to the poor security offered by these devices. © 2023, The Authors. All rights reserved.

关键词： Bluetooth

来源：评论

学校读者我要写书评

暂无评论

Blockchain Revolution: Empowering the Electric Vehicle Industry through Integration and Case Study Analysis

Blockchain Revolution: Empowering the Electric Vehicle Indus...

引用

IEEE Conference on Vehicular Technology (VTC)

作者： Ajmery Sultana Md Moniruzzaman Lian Zhao Dept. of Computer Science Algoma University Brampton Canada Dept. of Software Engineering Lakehead University Thunder Bay Canada Dept. of Electrical Computer and Biomedical Eng. Toronto Metropolitan University Toronto Canada

In the rapidly evolving landscape of electric vehicles (EVs), blockchain technology emerges as a transformative force, empowering the industry with enhanced security, transparency, and efficiency in transactions and energy management. However, the successful integration of blockchain technology in the context of EV is still in its infancy. Thus, this work aims to provide a comprehensive study of this young field from a broader perspective. We first discuss the integration process of blockchain technology in the EV domain. Then we explore the potential applications of blockchain technology in enhancing the efficiency, reliability, and sustainability of EV infrastructure and discuss some of the promising research in each category. Finally, we provide a typical application scenario and its specific embodiment in the EV infrastructure and strive to shed light on all-inclusive future research directions, which may facilitate the integration of blockchain technology in the EV ecosystem from theory to practice.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Blockchain-Based Secure e-KYC Solution for Banking System

Blockchain-Based Secure e-KYC Solution for Banking System

引用

International Conference on Computational Intelligence and Communication Networks (CICN)

作者： Zoya Tabassum Sobiya Arsheen Khaleel Ahmad Gulcihan Ozdemir Dept. of Computer Science and Information Technology Maulana Azad National Urdu University Hyderabad India Informatics Institute Istanbul Technical University Istanbul Turkey

ISBN: (数字)9798331505264

ISBN: (纸本)9798331505271

Blockchain technology offers a secured, digital, decentralized, ever-growing ledger that keeps records tamper-proof. The distributed ledger means that, even if one node is attacked or hacked, data may be accessed from other nodes, making the system more resistant to attacks and ensuring data availability. The hash function is used to strengthen the data integrity. E-KYC stands for electronic Know Your Customer, a way to verify a customer's identity. The banks frequently require the customer's identity documents for verification. Therefore, they spend an unwanted cost, effort, and abundant time during the KYC process. Sometimes, the information stored locally can be misleading. With unique features, blockchain-enabled e-KYC systems can protect sensitive data, reduce data breach risks, and ensure the integrity and confidentiality of e-KYC procedures. With its distributed ledger, blockchain technology stores e-KYC data across nodes and cryptographic techniques and can effectively increase e-KYC safety. Decentralization and immutability make blockchain technology a strong foundation for securing sensitive customer data. Strong authentication and public key cryptographic methods to protect e-KYC data.

关键词： Resistance Hash functions Costs Distributed ledger Data integrity Data breach Public key cryptography Blockchains Safety Computational intelligence

来源：评论

学校读者我要写书评

暂无评论

Instance-Level Safety-Aware Fidelity of Synthetic Data and its Calibration

Instance-Level Safety-Aware Fidelity of Synthetic Data and i...

引用

International Conference on Intelligent Transportation

作者： Chih-Hong Cheng Paul Stöckel Xingyu Zhao Dept. of Computer Science & Engineering Chalmers & Univ. of Gothenburg Sweden Department of Informatics University of Hildesheim Germany WMG University of Warwick United Kingdom

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

Modeling and calibrating the fidelity of synthetic data is paramount in shaping the future of safe and reliable self-driving technology by offering a cost-effective and scalable alternative to real-world data collection. We focus on its role in safety-critical applications, introducing four types of instance-level fidelity that go beyond mere visual input characteristics. The aim is to ensure that applying testing on synthetic data can reveal real-world safety issues, and the absence of safety-critical issues when testing under synthetic data can provide a strong safety guarantee in real-world behavior. We suggest an optimization method to refine the synthetic data generator, reducing fidelity gaps identified by deep learning components. Experiments show this tuning enhances the correlation between safety-critical errors in synthetic and real data.

关键词： Visualization Correlation Semantics Optimization methods Data collection Generators Safety Reliability Synthetic data Testing

来源：评论

学校读者我要写书评

暂无评论

Multicluster Kernel Intuitionistic Fuzzy C-Means and State Transition Algorithm : Framework for Low Light Segmentation Imaging of Tuberculosis Bacilli Base of Semisupervised Approach

Multicluster Kernel Intuitionistic Fuzzy C-Means and State T...

引用

IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Sari Ayu Wulandari I Ketut Eddy Purnama Eko Mulyanto Yuniarno Mauridhi Hery Purnomo Dept. of Electrical Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia Dept. of Biomedical Engineering Faculty of Electrical Engineering Universitas Dian Nuswantoro Semarang Indonesia Dept. of Electrical Engineering Dept. of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350319545

ISBN: (纸本)9798350319552

Annotated images are required as ground truth for deep learning. Bacterial segmentation is requires a lot of time and effort when done manually. The autosegmentation task gets more challenging since bacterial images contain low light properties, which have an important effect on auto annotating tasks. In order to solve this issue, we present a system that includes a fuzzy-based clustering method that enhances bacterial object segmentation performance by utilizing the multicluster idea. The State Transform Algorithm (STA) is used to obtain starting centroids in order to increase stability, because the Kernel of Intuitionistic Fuzzy C- Means (KIFCM) is sensitive to starting centroids and hence sensitive to being stuck in local optima. The accuracy of KIFCM-STA with bicluster is poor in low-light images. To boost performance, the multicluster technique (MKIFCM-STA) is presented as a continuation hybrid of KIFCM-STA. This framework allows for the ideal amount of clusters (Silhouette) and cluster ranking to provide clusters containing bacterial objects (Topsis). In order to compare our method against four prior approaches (IFCM, KFCM, KIFCM, and KIFCM-STA), we compare its qualitative aspects (visualization of images) and quantitative aspects (average IOU, Dice, HD, ASD, and Accuracy). In low light image clustering tasks, our model significantly improves and achieves great results in terms of accuracy, with a score of 89.438%. This accomplishment highlights how crucial it is that our framework tackles the problem of low-light image clustering in images of bacteria, eventually improving the image auto-annotation procedure.

关键词： Deep learning Image segmentation Visualization Microorganisms Accuracy Clustering methods Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

Impact of Machine Learning-Driven Predictive Models on Patient Outcomes in Modern Healthcare Systems

Impact of Machine Learning-Driven Predictive Models on Patie...

引用

Advances in Computing, Communication and Networking (ICAC2N), International Conference on

作者： Madhuri Sharma Rishikesh Kumar Gautam Medhavi Shukla Jitendra Kumar Ajay Pal Singh S. Yaminipriya Dept. of Life Sciences CHRI Campus Gwalior India Dept. of Humanities & S.Science Madhav University Pindwara India Dept. of Computer Science J.S. University Shikohabad India Dept. of Pharmacy Lingayas Vidyapeeth Faridabad India Dept. Biomedical Engineering Dhanalakshmi Srinivasan College Coimbatore India

ISBN: (数字)9798350356816

ISBN: (纸本)9798350356823

Traditional healthcare systems often struggle to meet the diverse needs of patients, leading to inefficiencies and less-than-optimal outcomes. The integration of machine learning (ML) is transforming healthcare by focusing on value-based care and enabling personalized, effective treatments. Modern healthcare devices are equipped with applications that collect and store comprehensive patient data, forming the basis for ML-driven predictive *** research investigates the transformative impact of ML in healthcare, highlighting its ability to improve patient care and optimize resource allocation. A proposed predictive model utilizes patient data and key parameters to forecast diseases, leveraging extensive datasets from diverse populations. These tools empower healthcare providers to identify and manage high-risk cases proactively, improving outcomes while streamlining care delivery *** study also explores the broader implications of ML adoption in value-based healthcare systems. By emphasizing personalized and proactive interventions, it demonstrates how ML-powered models can revolutionize traditional practices. The integration of ML in healthcare offers efficient, patient-centric solutions, enhancing the responsiveness and capacity of healthcare systems to meet growing patient demands and address complex medical challenges effectively.

关键词： Logistic regression Technological innovation Accuracy Medical services Transforms Predictive models Data models Diabetes Resource management Diseases

来源：评论

学校读者我要写书评

暂无评论

Pathology Report Generation and Multimodal Representation Learning for Cutaneous Melanocytic Lesions

arXiv

引用

arXiv 2025年

作者： Lucassen, Ruben T. Moonemans, Sander P.J. van de Luijtgaarden, Tijn Breimer, Gerben E. Blokx, Willeke A.M. Veta, Mitko Dept. of Pathology University Medical Center Utrecht Utrecht Netherlands Dept. of Biomedical Engineering Eindhoven University of Technology Eindhoven Netherlands Dept. of Mathematics and Computer Science Eindhoven University of Technology Eindhoven Netherlands Eindhoven University of Technology Eindhoven Netherlands

Millions of melanocytic skin lesions are examined by pathologists each year, the majority of which concern common nevi (i.e., ordinary moles). While most of these lesions can be diagnosed in seconds, writing the corresponding pathology report is much more time-consuming. Automating part of the report writing could, therefore, alleviate the increasing workload of pathologists. In this work, we develop a vision-language model specifically for the pathology domain of cutaneous melanocytic lesions. The model follows the Contrastive Captioner framework and was trained and evaluated using a melanocytic lesion dataset of 42,512 H&E-stained whole slide images and 19,645 corresponding pathology reports. Our results show that the quality scores of model-generated reports were on par with pathologist-written reports for common nevi, assessed by an expert pathologist in a reader study. While report generation revealed to be more difficult for rare melanocytic lesion subtypes, the cross-modal retrieval performance for these cases was considerably better. Copyright © 2025, The Authors. All rights reserved.

关键词： Visual languages

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：