检索结果-内蒙古大学图书馆

7th International Conference on Image information Processing, ICIIP 2023

作者： Sujatha, P. Saravanan, K. Sohail, Mohammed Ali Basi Reddy, A. Dixit, Rohit R. Krishnaiah, Nallam Amrita Vishwa Vidyapeetham Department of AI/ML Guntur Amaravati India R.M.K Engineering College Department of Information Technology Tamil Nadu Tiruvallur District India Jazan University College of Computer Science & Information Technology Department of Computer & Network Engineering Jazan Saudi Arabia Mohan Babu University School of Computing Department of Computer Science And Engineering Andhra Pradesh Tirupati India Siemens Healthineers NH03755 United States St.Martin's Engineering College Department of Ai&ml Secunderabad Telangana Dhulapally500100 India

ISBN: (纸本)9798350371406

The potential of drug combinations to treat and overcome medication resistance complex genetic diseases is evident. Synergistic drug combinations offer a promising way to enhance drug therapy efficacy and reduce the required medication dosage. However, developing effective combination medication therapies with synergistic effects has been challenging, despite numerous ongoing clinical investigations. Current models and approaches to detect medication synergy outlined in the literature lack the expected consistency in outcomes. to better comprehend the impact of particular medication combinations, it is essential to be familiar with the vocabulary used to describe synergy. In this study, a combinational drug screen is utilized to identify useful features for locating synergistic or efficient drug combinations. The feature selection algorithm (Boruta) helps select the most relevant features, and machine learning models are then trained using the selected feature dataset. Performance assessment metrics like sensitivity, accuracy, and specificity are used to compare the trained models, and the Random Forest model stands out for its significantly better performance compared to other models. © 2023 IEEE.

关键词： Drug dosage

来源：评论

学校读者我要写书评

暂无评论

Speed-Aware Flow Management with Packet Classification to Mitigate Congestion in VANETs

Speed-Aware Flow Management with Packet Classification to Mi...

引用

2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023

作者： Wang, You-Chiun Ho, Cheng-En National Sun Yat-sen University Department of Computer Science and Engineering Kaohsiung Taiwan National Sun Yat-sen University Information Security Research Center Kaohsiung Taiwan

ISBN: (纸本)9798350316803

Due to service diversity, there may be many packet flows with different urgency and importance in a vehicular ad hoc network (VANET). In a traffic jam, numerous vehicles vie to send packets, which leads to network congestion. Moreover, when accidents occur, the vehicles detecting them will broadcast safety-critical messages to warn others, which could worsen congestion and thus cause the loss of many messages. To this end, the paper proposes a speed-aware flow management with packet classification (SFM-PC) scheme. In SFM-PC, packets will be classified by their services. According to its speed, each vehicle gauges the traffic conditions locally and adjusts the transmission rate of packets by itself. On receiving the packets of safety-critical messages, vehicles use packet consolidation to reduce the dissemination of duplicate messages. Through simulations, we demonstrate that the SFM-PC scheme can efficiently mitigate congestion in a VANET, where it has a much lower packet loss rate than other methods. © 2023 IEEE.

关键词： Vehicular ad hoc networks

来源：评论

学校读者我要写书评

暂无评论

Enhancing Performances of Deep Neural networks with Ensemble Learning Methods for Complex Human Activity Recognition Using Wearable Sensors 10

Enhancing Performances of Deep Neural Networks with Ensemble...

引用

10th International Conference on Digital Arts, Media and Technology and 8th ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications engineering, ECTI DAMT and NCON 2025

作者： Mekruksavanich, Sakorn Jitpattanakul, Anuchit University of Phayao School of Information and Communication Technology Department of Computer Engineering Phayao Thailand King Mongkut's University of Technology North Bangkok Intelligent and Nonlinear Dynamic Innovations Research Center Department of Mathematics Faculty of Applied Science Bangkok Thailand

ISBN: (纸本)9798331543273

Sensor-based human activity recognition (HAR) is a widely explored research area focused on identifying human behaviors by analyzing sensor-generated data, particularly one-dimensional time series signals. Such HAR systems have many real-world applications, including elderly health monitoring and athlete performance evaluation. This paper presents Ens-DeepNet, a novel ensemble learning approach designed for recognizing complex human activities using data from wearable sensors. While deep neural networks have proven effective for HAR tasks, their performance can be further improved through ensemble strategies. To this end, we propose an ensemble architecture that combines five distinct deep learning models - convolutional neural network (CNN), long short-term memory (LSTM), bidirectional LSTM (BiLSTM), gated recurrent unit (GRU), and bidirectional GRU (BiGRU). These models are integrated using a majority voting scheme to boost classification accuracy. The proposed method is evaluated using the UTwente dataset, which includes sensor data collected from ten individuals via tri-axial accelerometers and gyroscopes. Experimental findings demonstrate that the ensemble model achieves an impressive accuracy of 99.28%, surpassing the performance of each standalone model, whose accuracies range from 92.77%to 97.34%. This performance gain is particularly notable in recognizing complex activities such as eating, drinking coffee, smoking, and conversing. © 2025 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

FedMonitor: An Implementation Architecture for Monitoring of Resources and Events'Notifications on Federated Cloud Computing Infrastructures 4

FedMonitor: An Implementation Architecture for Monitoring of...

引用

4th International Conference on Emerging Trends in networks and computer Communications, ETNCC 2024

作者： Adetiba, Emmanuel Nnaji, Uche Wejin, John S. Ojesanmi, Festus Akanle, Matthew B. Ajayi, Priscilla O. Sweetwiliams, Faith O. Thakur, Surendra C. Adebiyi, Ezekiel F. Department of Electrical and Information Engineering and Covenant Applied Ota Nigeria HRA Institute for Systems Science Durban University of Technology Durban South Africa Covenant University Department of Computer and Information Science & CApIC-ACE Ota Nigeria Covenant University Department of Electrical and Information Engineering & CApIC-ACE Jalingo Nigeria Tareba State University Department of Computer Science Jalingo Nigeria Ota Nigeria Covenant University & CApIC-ACE Covenant University Department of Electrical and Information Engineering Ota Nigeria Covenant University Center for Systems and Information Services & CApIC-ACE Ota Nigeria Durban University of Technology e-Skills Co-Laboratory Department of Information Technology and KZN Durban4001 South Africa Covenant University Ogun State Ota Nigeria Makerere University African Center of Excellence in Bioinformatics & Data Intensive Science Kampala10218 Uganda

ISBN: (纸本)9798350353266

In the evolving landscape of cloud computing, federated cloud infrastructures present unique challenges and opportunities for resource and application monitoring. Monitoring the diverse array of cloud resources and applications within a federated cloud environment is crucial for delivering consistent Quality of Service (QoS) and continuous oversight across various cloud applications and infrastructure. Despite the various successes documented in the literature on multi-cloud monitoring, existing frameworks have not fully explored or provided enough insights into centralized monitoring of resources, applications, and network devices in a federated cloud environment. This paper introduces FedMonitor, an implementation architecture designed to enhance the monitoring and notification capabilities in federated cloud environments by building on the theoretical ideals in our earlier work (i.e. FEDARGOS-V1). FedMonitor leverages Prometheus and Grafana to crawl, manage and visualize metrics from diverse software services, hardware resources, and network devices within a federated cloud environment. The results demonstrate hat FedMonitor improves the effectiveness of resource and application monitoring in federated cloud environments. © 2024 IEEE.

关键词： Cloud platforms

来源：评论

学校读者我要写书评

暂无评论

Adaptive Countermeasure by Credibility to Defend SDN Controllers Against BlackNurse-SC Attacks 12

Adaptive Countermeasure by Credibility to Defend SDN Control...

引用

12th IEEE International Conference on Communication, networks and Satellite, COMNETSAT 2023

作者： Wang, You-Chiun Wang, Pin-Yuan National Sun Yat-sen University Department of Computer Science and Engineering Kaohsiung Taiwan National Sun Yat-sen University Information Security Research Center Kaohsiung Taiwan

ISBN: (纸本)9798350341102

Software-defined networking (SDN) facilitates network management by using a controller to monitor the network status and regulate switches. Owing to its central control nature, the controller often becomes the target of attacks. BlackNurse-SC, an emerging type of DDoS attack, drains the controller of its computing resources via ICMP error messages and causes a disruption in the SDN network. To defend the controller against BlackNurse-SC attacks, we propose an adaptive countermeasure by credibility (ACC) that checks if hosts have suspected attacking behavior and assesses their credibility. Low-credibility hosts will have their ICMP packets blocked as a penalty, and the penalty duration is adjusted depending on the degree of credibility. In addition, the credibility of a host can be restored when it doesn't send ICMP error messages for a while. Simulation results reveal that the ACC scheme can protect a controller from BlackNurse-SC attacks effectively. © 2023 IEEE.

关键词： Controllers

来源：评论

学校读者我要写书评

暂无评论

The influence of culture on creativity in ideation: a review

The influence of culture on creativity in ideation: a review

引用

2024 International Design Society Conference, Design 2024

作者： Gong, Zhengya Gonçalves, Milene Nanjappan, Vijayakumar Georgiev, Georgi V. Center for Ubiquitous Computing University of Oulu Finland Department of Design Organisation and Strategy Faculty of Industrial Design Engineering Delft University of Technology Netherlands School of Computer Science and Information Technology University College Cork Ireland

The relationship between culture and creativity has sparked the interest of researchers for decades. Although researchers have attempted to establish a connection between culture and creativity, the precise relationship between the two remains ambiguous. The current paper examined extant literature on the subject matter and synthesized the relations between culture and creativity in ideation over the past twenty years. The present study expounds upon the utilized samples, measures implemented to assess creativity and culture, and the study results. © 2024 Proceedings of the Design Society. All rights reserved.

关键词： Behavioral research

来源：评论

学校读者我要写书评

暂无评论

APP: Enabling Soft Real-Time Execution on Densely-Populated Hybrid Memory System 23

APP: Enabling Soft Real-Time Execution on Densely-Populated ...

引用

Proceedings of the 60th Annual ACM/IEEE Design Automation Conference

作者： Zheng-Wei Wu Yun-Chih Chen Yuan-Hao Chang Tei-Wei Kuo Department of Computer Science and Information Engineering National Taiwan University Institute of Information Science Academia Sinica Taiwan Department of Computer Science and Information Engineering National Taiwan University and Mohamed bin Zayed University of Artificial Intelligence Department of Computer Science and NTU High Performance and Scientific Computing Center National Taiwan University

ISBN: (纸本)9798350323481

Memory swapping was considered slow and evil, but swapping to Ultra Low-Latency storage like Optane has become a promising solution to save power and cost, helping densely-populated edge server to overcome its DRAM capacity bottleneck. However, the lack of integration between CPU scheduling and memory paging causes soft real-time tasks running on edge servers to miss deadlines under heavy memory multiplexing. We propose APP (Adaptive Page Pinning), lightweight protection of working set memory to ensure meeting soft real-time task deadlines without starving other non-real-time tasks. Experiments show that APP alleviates thrashing in memory-intensive tasks and upholds soft real-time task deadlines.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An Automated Platform for Gathering and Managing Open-Source Cyber Threat Intelligence 2

An Automated Platform for Gathering and Managing Open-Source...

引用

2nd International Conference on Business Analytics for Technology and Security, ICBATS 2023

作者： Al-Dmour, Nidal A. Kamrul Hasan, Mohammad Ajmal, Masood Ali, Muhammad Naseer, Iftikhar Ali, Atif Hamadi, Hussam Al Ali, Nasir Mutah University College of Engineering Department of Computer Engineering Jordan Center for Cyber Security Malaysia Riphah International University Islamabad Pakistan University of Central Punjab Pakistan The Superior University Faculty of Computer Science & Information Technology Lahore Pakistan Cyberjaya Malaysia College of Engineering and IT University of Dubai United Arab Emirates School of Computer Science NCBA&E Lahore Pakistan Applied Science Private University Applied Science Research Center Amman11937 Jordan

ISBN: (纸本)9798350335644

The community has begun paying more attention to source OSCTI Cyber Threat Intelligence to stay informed about the rapidly changing cyber threat landscape. Numerous reports from the OSCTI frequently provide information about dangers. However, current OSCTI gathering and management tools have mainly concentrated on individual minor compromise indicators, despite the urgent need for high-quality OSCTI. The relationship between higher-level notions (including the strategies, methods, and processes) and the connections between them, which hold crucial information about dangerous behaviors and are crucial to revealing the full dangerous situation, have been disregarded. Therefore, we present SecurityKG, an automated OSCTI collection and administration system. SecurityKG collects OSCTI to extract high-fidelity knowledge about threat behaviours to address the void. Using a mixture of AI and NLP approaches, a security know-how graph is then constructed from a wide variety of sources. To facilitate knowledge graph exploration, SecurityKG provides a user interface (UI) that supports multiple forms of interactivity. © 2023 IEEE.

关键词： User interfaces

来源：评论

学校读者我要写书评

暂无评论

Pied kingfisher optimizer: a new bio-inspired algorithm for solving numerical optimization and industrial engineering problems

引用

Neural Computing and Applications 2024年第25期36卷 15455-15513页

作者： Bouaouda, Anas Hashim, Fatma A. Sayouti, Yassine Hussien, Abdelazim G. LSIB Laboratory FST Mohammedia Hassan II University of Casablanca Mohammedia Morocco Faculty of Engineering Helwan University Cairo Egypt MEU Research Unit Middle East University Amman11831 Jordan Department of Computer and Information Science Linköping University Linköping Sweden Faculty of Science Fayoum University Faiyum Egypt Applied Science Research Center Applied Science Private University Amman Jordan

In this study, we introduce the pied kingfisher optimizer (PKO), a novel swarm-based meta-heuristic algorithm that draws inspiration from the distinctive hunting behavior and symbiotic relationships observed in pied kingfishers in the natural world. The PKO algorithm is structured around three distinct phases: perching/hovering for prey (exploration/diversification), diving for prey (exploitation/intensification), and fostering symbiotic relations. These behavioral aspects are translated into mathematical models capable of effectively addressing a wide array of optimization challenges across diverse search spaces. The algorithm’s performance is rigorously evaluated across thirty-nine test functions, which encompass various unimodal, multimodal, composite, and hybrid ones. Additionally, eight real-world engineering optimization problems, including both constrained and unconstrained scenarios, are considered in the assessment. To gauge PKO’s efficacy, it is subjected to a comparative analysis against 3 categories of rival optimizers. The 1st category comprises well-established and widely-cited optimizers such as particle swarm optimization and genetic algorithm. The 2nd category encompasses recently published algorithms, including Harris Hawks optimization, Whale optimization algorithm, sine cosine algorithm, Grey Wolf optimizer, gravitational search algorithm, and moth-flame optimization. The 3rd category includes advanced algorithms, such as covariance matrix adaptation evolution strategy and Ensemble Sinusoidal Differential Covariance Matrix Adaptation with Euclidean Neighborhood (LSHADE-cnEpSin). The comparative analysis employs various performance metrics, including the Friedman mean rank and the Wilcoxon rank-sum test, to reveal PKO’s effectiveness and efficiency. The overall results highlight PKO’s exceptional ability to tackle intricate optimization problems characterized by challenging search spaces. PKO demonstrates superior exploration and exploitation tend

关键词： Global optimization

来源：评论

学校读者我要写书评

暂无评论

The Image of Numerals with Calibration on TVM

The Image of Numerals with Calibration on TVM

引用

computer science, computer engineering, & Applied Computing (CSCE), Congress in

作者： Ssu-Hsuan Lu Department of Computer Information and Network Engineering Lunghwa University of Science and Technology Taoyuan Taiwan

Today's open-source deep learning frameworks, such as TensorFlow, PyTorch, TVM, and Caffe, have become widely used tools for deep learning and support hardware accel-erators like GPU and TPU. Among these platforms, TVM stands out for its flexibility and compatibility by compiling high-level deep learning frameworks (such as TensorFlow, PyTorch, etc.) to generate optimized low-level code, which can be automatically optimized to improve performance. Although CNN significantly affects image recognition, some images may not be correctly recognized due to problems such as location, orientation, and deformation. Therefore, this paper aims to improve recognition accuracy by normalizing images. This paper focuses on developing an image normalization calibration module on TVM with OpenCV and performing recognition for digital photos. This module is mainly responsible for edge detection and performing normalization adjustments based on the selected preprocessing areas.

关键词：

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：