检索结果-内蒙古大学图书馆

16th International Conference on COMmunication Systems and NETworkS, COMSNETS 2024

作者： Tapadar, Karnish N A Khatua, Manas Tamarapalli, Venkatesh Indian Institute of Technology Guwahati Dept. of Computer Science and Engineering India

ISBN: (纸本)9798350383119

The 6TiSCH standard uses IEEE 802.15.4 Time Slotted Channel Hopping (TSCH) as a MAC layer protocol. TSCH cell scheduling determines packet transmission schedules in terms of timing and channel allocation. The Minimal Scheduling Function (MSF) and the 6P protocol facilitate schedule management dynamically. MSF involves a decision-making process to add/delete one cell at a time from the current schedule to adapt the schedule to modified traffic rate. The cell deletion is accomplished by randomly selecting one of the scheduled cells between two communicating nodes. However, random cell deletion can elevate end-to-end latency and energy consumption. Therefore, this paper proposes a Latency-aware Cell Deletion (LCD) mechanism to minimize associated average end-to-end latency and energy consumption. Simulations using the 6TiSCH simulator verified that in an 80-node network, compared to the standard MSF and another benchmark scheme IMSF, LCD achieved a substantial 44.40% and 42.39% reduction in end-to-end latency, respectively. © 2024 IEEE.

关键词： 6TiSCH Network Adaptive Link Scheduling Link Scheduling Minimal Scheduling Function

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Feature Selection Methods for Software Bug Classification

Comparative Analysis of Feature Selection Methods for Softwa...

引用

2024 International Conference on science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Orenyi, Bajeh Amos Oluwambo Tolulope, Olowe Tobi, Asani Emmanuel University of Ilorin Dept. of Computer Science Ilorin Nigeria Landmark University Dept. of Computer Science Omuaran Nigeria

ISBN: (纸本)9798350358155

Software bug classification is a critical task in software engineering aimed at identifying defects early to improve software quality and reliability. Despite its importance, effectively classifying software defects remains a challenge, necessitating the use of advanced techniques such as feature selection. This research presents a comprehensive study on feature selection methods for software defect classification, to evaluate their effectiveness in enhancing classification accuracy. The study investigates the impact of feature selection methods (filter-based, wrapper-based, and embedding) on model performance using classification algorithms such Naïve Bayes, Support Vector Machines, K-Nearest Neighbour, and Random Forest. The studies are carried out using publicly accessible software defect datasets, and conventional evaluation measures such as accuracy, precision, recall, and F1-score are used to evaluate the effectiveness of each feature selection strategy. The findings of the study confirm the effectiveness of ensemble methods in bug severity classification, with Random Forest achieving notable accuracy rates for different datasets. Additionally, the study highlights the superiority of wrapper feature selection techniques over filter methods, demonstrating their ability to select informative features for defect severity classification. The findings of this work give useful information for practitioners in selecting and implementing feature selection approaches when developing defect classification models, ultimately contributing to the enhancement of software quality and reliability. © 2024 IEEE.

关键词： Software quality

来源：评论

学校读者我要写书评

暂无评论

Key Vertex Pairs Extraction for Graph Classification Based on Probability Distribution Learning 6

Key Vertex Pairs Extraction for Graph Classification Based o...

引用

6th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2024

作者： Huang, Jianming Kasai, Hiroyuki WASEDA University Dept. of Computer Science and Communication Engineering Tokyo Japan

ISBN: (纸本)9798350344349

Graph classification is a hot topic of machine learning for graph-structured data, and it is also a very potential and valuable research. However, the difficulty of graph classification is challenging and special, which is quite different from the normal classification problems. One of the most difficult points of graph classification is that the numbers of vertex neighbors in graphs are usually variable, which makes the number of weights uncertain and ambiguous. Recent work such like the graph attention network apply the transformer on the graph neural network. However, the learned attentions cannot strictly reveal the importance of each part of graph, which makes the model less explainable. Moreover, for small datasets, it performs less effectively because of the excessive parameters. In order to overcome these difficulties, we propose a lightweight model with an edge weighting function based on the probability distributions of node pair features learned by the Gaussian mixture model. Although the proposed framework is simple, the experimental results shows its effectiveness on small datasets. © 2024 IEEE.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Review of Media Forensics and Deepfake Detection Technique 10

A Comprehensive Review of Media Forensics and Deepfake Detec...

引用

17th INDIACom;2023 10th International Conference on Computing for Sustainable Global Development, INDIACom 2023

作者： Kandari, Megha Tripathi, Vikas Pant, Bhaskar Dept. of Computer Science and Engineering Dehradun India

ISBN: (纸本)9789380544472

In recent years, as the use of the internet and social media has advanced, so the number of fake media content also grows rapidly. Media forensic techniques are becoming essential to analyze and extract information from various types of media, such as images, videos, and audio recordings, to be used as evidence in legal proceedings. As of recent trends, social media is being flooded with sophisticated deepfakes. So evolving deepfake detection technique is required to curb the flow of misinformation via deepfake videos. This paper intends to present a review of evolving media forensics and deepfake detection techniques. © 2023 Bharati Vidyapeeth, New Delhi.

关键词： Social networking (online)

来源：评论

学校读者我要写书评

暂无评论

Prosecutorial Outcome Predication with LoRA and QLoRA 37

Prosecutorial Outcome Predication with LoRA and QLoRA

引用

37th Annual Conference on Legal Knowledge and Information Systems, JURIX 2024

作者： Chien, Kuo-Chun Chang, Chia-Hui Huang, Huai-Hsuan Kung, Jo-Chi Dept. of Computer Science & Information Engineering National Central University Taiwan

ISBN: (纸本)9781643685625

Our study on Legal Judgment Prediction (LJP) focuses on indictments, designing innovative tasks for prosecutors to predict reasons, imprisonment, fines, and penalty types. We investigated multi-task learning (MTL), Low-Rank Adaptation (LoRA), and its quantized version (QLoRA). Results show that the MTL framework, combined with LoRA and QLoRA, excels in prediction while optimizing resource use. Error analysis in the Reason field of TWPJD dataset was conducted to guide future predictions. Future work will focus on balancing sub-task performance and collecting more investigative data to enhance legal AI applications. © 2024 The Authors.

关键词： Multi-task learning

来源：评论

学校读者我要写书评

暂无评论

Machine Learning-Powered Defense Against Phishing Websites

Machine Learning-Powered Defense Against Phishing Websites

引用

2024 IEEE International Students' Conference on Electrical, Electronics and computer science, SCEECS 2024

作者： Dwivedi, Dipesh Ahmed, Sajjad Patel, Adarsh Azath, H. Vit University Dept. of Computer Science and Engineering Sehore466114 India

ISBN: (纸本)9798350348460

The proliferation of phishing URLs has experienced rapid growth in recent years, necessitating urgent attention to phishing attack detection in cybersecurity. In response, we introduce an improved predictive model that leverages both machine learning and a Deep Learning Model. Our dataset consists of 88,674 instances, encompassing 112 features, including the class level. Notably, this dataset comprises 58,000 legitimate instances and 30,647 phishing *** proposed method incorporates six distinct algorithms: Decision Tree, Support Vector Machine, K-nearest neighbors, Logistic Regression, Ensemble Classifier, and Neural Network algorithm. we systematically evaluated total 28 models performance with different types of feature changes. Following enhancements, every algorithm demonstrated an accuracy performance surpassing 93.16%. Among them, the Ensemble Classifier emerged as the most effective, boasting an accuracy 97.45%, MCC 94.37%, precision a96.35%, and an F1 Score 96.31%. © 2024 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Seamless Service Evolution: Enhancing Customer Satisfaction Using AWS-Driven AI Chatbots for Restaurant Ordering 4

Seamless Service Evolution: Enhancing Customer Satisfaction ...

引用

4th International Conference on Sustainable Expert Systems, ICSES 2024

作者： Ali, Mohammed Jaffer Vyshnavi, M.R.V. Kumar, Konda V.S. Harshith Vishnubhatla, Sravya Rajagopal, Shinu M. Amrita School of Computing Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331540364

In the current restaurant business environment, factors have emerged in the manner in which consumers are attended to and the ways orders are placed. As good as these traditional systems may be, they do not offer the optimum flexibility and consumer convergence that today's client demands for fast and convenient services. Recent approaches using only basic form of automation and rule-based chatbots do offer some enhancements but lack adequate capabilities to deal with huge volumes of orders, custom recommendations and scalability according to demand. Further, the existing systems have problems with scalability, versatility to different customers' trends and needs, and real-time interactions. To overcome these challenges our work, will utilize modern advances in artificial intelligence and cloud technology. The proposed system uses Amazon Lex for NLU, A WS Lambda for processing multiple booking requests simultaneously without any intervention from the users and Amazon Polly for making interaction more interactive with personalized audio. In addition, Amazon Rekognition and A WS S3 for images will be used for analysis of images and proper storage of data respectively, enhancing the customer satisfaction by recommending products based on a past order. All these technologies integrated with A WS ecosystem in our solution will provide convenience, efficiency and passion to restaurant business proprietors to fulfill the increasing demands of modern customer. The system also supports linkage with some commonly used applications such as WhatsApp, guaranteeing that the customers receive timely updates. Thus, this solution is designed to create an improved status of restaurant ordering and eliminate the problematic experiences placed in current schemes. © 2024 IEEE.

关键词： Scalability

来源：评论

学校读者我要写书评

暂无评论

Flatness Improvement Technology of Febry-Perrot Interferometer via Simultaneous Modulation of 3-Channel PZT Actuators and Interface Electronics Implementation

引用

Transactions of the Korean Institute of Electrical Engineers 2024年第5期73卷 827-833页

作者： Park, Jung-Woong Jeong, Sang-Won Lee, Hyun-Ho Jang, Min-Jun Lee, Keekeun Dept. of Electrical and Computer Engineering Ajou University Korea Republic of Dept. of Electrical and Computer Engineering Ajou University Korea Republic of J&C Technology Co. Gimcheon-si Korea Republic of

This study presents the development of a lead zirconate titanate (PZT)-based Febry-Perrot Interferometer (FPI) tailored for the selective transmission of specific wavelengths. Our FPI integrates two mirrors, 3-channel PZT actuators, and interfacing electronics, enabling dynamic adjustments in PZT actuator lengths through voltage application. The interface electronics facilitate precise voltage control over the multi-channel PZT actuators, regulating the air gap between mirrors. Experimental results demonstrate the effectiveness of the developed interfacing electronics in modulating the transmission peak of light, resulting in a narrowed full width at half maximum (FWHM) and a heightened transmittance rate at targeted wavelengths. Additionally, the interface adept.y manages multi-channel PZT voltages, mitigating potential mirror alignment discrepancies during FPI assembly. By optimizing the air gap between the mirrors, significant enhancements in the center wavelength of the transmitted beam are achieved. Copyright © The Korean Institute of Electrical Engineers.

关键词： Actuators

来源：评论

学校读者我要写书评

暂无评论

Estimating Post-Synaptic Effects for Online Training of Feed-Forward SNNs

Estimating Post-Synaptic Effects for Online Training of Feed...

引用

2024 International Conference on Neuromorphic Systems, ICONS 2024

作者： Summe, Thomas M. Schaefer, Clemens JS Joshi, Siddharth University of Notre Dame Dept. of Computer Science and Engineering United States

ISBN: (纸本)9798350368659

Facilitating online learning in spiking neural networks (SNNs) is a key step in developing event-based models that can adapt to changing environments and learn from continuous data streams in real-time. Although forward-mode differentiation enables online learning, its computational requirements restrict scalability. This is typically addressed through approximations that limit learning in deep models. In this study, we propose Online Training with Postsynaptic Estimates (OTPE) for training feed-forward SNNs, which approximates Real-Time Recurrent Learning (RTRL) by incorporating temporal dynamics not captured by current approximations, such as Online Training Through Time (OTTT) and Online Spatio-Temporal Learning (OSTL). We show improved scaling for multi-layer networks using a novel approximation of temporal effects on the subsequent layer's activity. This approximation incurs minimal overhead in the time and space complexity compared to similar algorithms, and the calculation of temporal effects remains local to each layer. We characterize the learning performance of our proposed algorithms on multiple SNN model configurations for rate-based and time-based encoding. OTPE exhibits the highest directional alignment to exact gradients, calculated with backpropagation through time (BPTT), in deep networks and, on time-based encoding, outperforms other approximate methods. We also observe sizeable gains in average performance over similar algorithms in offline training of Spiking Heidelberg Digits with equivalent hyper-parameters (OTTT/OSTL - 70.5%;OTPE - 75.2%;BPTT - 78.1%). © 2024 IEEE.

关键词： Encoding (symbols)

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Techniques for Bangladeshi Coin Detection and Automated Counting System: A Comparative Study of Multiple Algorithms 3

Deep Learning Techniques for Bangladeshi Coin Detection and ...

引用

3rd International Conference on Advancement in Electrical and Electronic engineering, ICAEEE 2024

作者： Babor, Ashraf Hussan Choity, Umme Habiba Kaspia, Most. Paul, Subrata Kumer Paul, Rakhi Rani Haque, Md. Momenul Hamid, Md. Ekramul Qadirabad Dayarampur Dept. of Computer Science and Engineering Natore6431 Bangladesh University of Rajshahi Department of Computer Science and Engineering Rajshahi6205 Bangladesh

ISBN: (纸本)9798350388282

Efficient currency detection and counting systems are crucial for the smooth operation of any financial ecosystem. This paper explores the development, implementation, and potential impact of a specialized currency detection and counting system for Bangladeshi coin currencies. Through this comprehensive study, this paper addresses the unique challenges and opportunities in Bangladesh's coin currency management landscape, highlighting the motivations and results of such a system's introduction. computer vision technology includes currency detection. In this paper, we present a coin currency detection system that can detect coin currency from images. Designing a CNN-based coin recognition system for the recognition of Bangladeshi coins of denominations '1tk', '2tk', and '5tk'. We have created a dataset that contains more than 10,000 images. We photographed coin currencies from both sides, and the system can recognize coin currencies from both sides. For high efficiency, we test on various backgrounds. Experimental results are presented successfully with a training accuracy of 99.99% with VGG16, 99.38% with VGG19, and 99.99% with EfficientNetB0. We also got validation accuracy with VGG16 of 90.90%, 99.96% with VGG19, and 99.51% with EfficientNetB0. © 2024 IEEE.

关键词： Deep learning

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：