检索结果-内蒙古大学图书馆

Designing Novel Cognitive Diagnosis Models via Evolutionary Multi-Objective Neural Architecture Search

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Yang, Shangshang Ma, Haiping Zhen, Cheng Tian, Ye Zhang, Limiao Jin, Yaochu Zhang, Xingyi The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Artificial Intelligence Anhui University Hefei230039 China The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Institutes of Physical Science and Information Technology Anhui University Hefei230601 China Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University Anhui Hefei230601 China The Faculty of Technology Bielefeld Unversity Bielefeld33619 Germany

Cognitive diagnosis plays a vital role in modern intelligent education platforms to reveal students’ proficiency in knowledge concepts for subsequent adaptive tasks. However, due to the requirement of high model interpretability, existing manually designed cognitive diagnosis models hold too simple architectures to meet the demand of current intelligent education systems, where the bias of human design also limits the emergence of effective cognitive diagnosis models. In this paper, we propose to automatically design novel cognitive diagnosis models by evolutionary multiobjective neural architecture search (NAS). Specifically, we observe existing models can be represented by a general model handling three given types of inputs and thus first design an expressive search space for the NAS task in cognitive diagnosis. Then, we propose multi-objective genetic programming (MOGP) to explore the NAS task’s search space by maximizing model performance and interpretability. In the MOGP design, each architecture is transformed into a tree architecture and encoded by a tree for easy optimization, and a tailored genetic operation based on four sub-genetic operations is devised to generate offspring effectively. Besides, an initialization strategy is also suggested to accelerate the convergence by evolving half of the population from existing models’ variants. Experiments on two real-world datasets demonstrate that the cognitive diagnosis models searched by the proposed approach exhibit significantly better performance than existing models and also hold as good interpretability as human-designed models. Copyright © 2023, The Authors. All rights reserved.

关键词： Multiobjective optimization

Interpreting Vulnerabilities of Multi-Instance Learning to Adversarial Perturbations

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Zhang, Yu-Xuan Meng, Hua Cao, Xue-Mei Zhou, Zhengchun Yang, Mei Adhikary, Avik Ranjan School of Information Science and Technology Southwest Jiaotong University Chengdu611730 China School of Computing and Artifical Intelligence Southwestern University of Finance and Economics Chengdu611130 China School of Computer Science Southwest Petroleum University Chengdu610500 China

Multi-instance Learning (MIL) is a recent machine learning paradigm which is immensely useful in various real-life applications, like image analysis, video anomaly detection, text classification, etc. It is well known that most of the existing machine learning classifiers are highly vulnerable to adversarial perturbations. Since MIL is a weakly supervised learning, where information is available for a set of instances, called bag and not for every instances, adversarial perturbations can be fatal. In this paper, we have proposed two adversarial perturbation methods to analyze the effect of adversarial perturbations to interpret the vulnerability of MIL methods. Out of the two algorithms, one can be customized for every bag, and the other is a universal one, which can affect all bags in a given data set and thus has some generalizability. Through simulations, we have also shown the effectiveness of the proposed algorithms to fool the state-of-the-art (SOTA) MIL methods. Finally, we have discussed through experiments, about taking care of these kind of adversarial perturbations through a simple strategy. Source codes are available at https://***/InkiInki/MI-UAP. Copyright © 2022, The Authors. All rights reserved.

关键词： Machine learning

A Trajectory Tracking System for Zebrafish Based on Embedded Edge Artificial Intelligence

学校读者我要写书评

暂无评论

A Trajectory Tracking System for Zebrafish Based on Embedded...

International Conference on Parallel and Distributed Systems (ICPADS)

作者： Chuanhao Zang Anming Dong Jiguo Yu Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China School of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Big Data Institute Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

Trajectory tracking of zebrafish is an important requirement in studying neurological disorders and developing new psychoactive drug. However, many challenges emerge for stable tracking, since zebrafish are similar in appearance, occlusion, agile, non-linear in moving and easy to swarm, all of which will lead to mistrack for multiple fish. And there is no precedent for tracking zebrafish through embedded edge artificial intelligence device. To overcome these difficulties, we present a tracking system for zebrafish based on RK3588-S. First, We construct an embedded edge AI hardware system consisting of two cameras driven by the RK3588-S, one for the front view and the other for top view of the fish. Then, we develop a 2D tracking algorithm based on YOLOv5 and the Observation-Centric Simple online and real-time tracking (OC-SORT) algorithm, which are transplanted to the RK3588-S for tracking the top and front views of the fish at the edge device. Compared with the previous methods, our method has fewer ID exchanges and highly real-time. Moreover, we apply the MQTT mechanism to establish communication links between the edge and the cloud to reliably transmit data to the cloud. The correspondence between cloud server and embedded AI is 1: N. Finally, we design a multi-view data fusion association algorithm to fuse the data of the two views in the cloud, which are further utilized to build the 3D tracklets of the zebrafish.

关键词：

An Optimized Design of Antenna Arrays for the Smart Antenna Systems

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2021年第11期69卷 1979-1994页

作者： Fahd N.Al-Wesabi Murad A.A.Almekhlafi Huda G.Iskandar Adnan Zain Saleh Alzahrani Mohammed Alamgeer Nadhem Nemri Sami Dhabi Mohammad Medani Ali.M.Al-Sharafi Department of Computer Science King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Electrical Engineering–Communication Engineering Sana’a UniversityYemen School of Computing Faculty of EngineeringUniversiti Teknologi MalaysiaMalaysia Department of Electronics and Communication Engineering Faculty of EngineeringUniversity of AdenYemen Department of Information Systems King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Department of Computer Science College of Computers and Information TechnologyUniversity of BishaKSA

In recent years,there has been an increasing demand to improve cellular communication services in several *** aspect that received the most attention is improving the quality of coverage through using smart antennas which consist of array *** paper investigates the main characteristics and design of the three types of array antennas of the base station for better coverage through simulation(MATLAB)which provides field and strength patterns measured in polar and rectangular coordinates for a variety of conditions including broadsides,ordinary End-fire,and increasing directivity End-fire which is typically used in smart *** method of analysis was applied to twenty experiments of process design to each antenna type separately,so sixty results were obtained from the radiation pattern indicating the parameters for each radiation ***,nineteen design experiments were described in this *** is hoped that the results obtained from this study will help engineers solve coverage problems as well as improve the quality of cellular communication networks.

关键词： Smart antenna antenna arrays patterns construction coverage

Implementing cryptographic internet of things in patient-centered network to vestige alzheimer and dementia patient

学校读者我要写书评

暂无评论

Implementing cryptographic internet of things in patient-cen...

作者： Kowsigan, M. Ramamoorthy, S. Amaran, Sibi Jeyabharathi, D. Department of Computer Science and Engineering School of Computing SRM Institute of Science and Technology Chennai India Department of Computer Science and Engineering SRM Institute of Science and Technology Kattankulathur India Department of Information Technology Sri Krishna College of Technology Coimbatore India

Structural information Guided Multimodal Pre-training for Vehicle-centric Perception

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Wang, Xiao Wu, Wentao Li, Chenglong Zhao, Zhicheng Chen, Zhe Shi, Yukai Tang, Jin Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University Hefei230601 China Anhui Provincial Key Laboratory of Multimodal Cognitive Computation Anhui University Hefei230601 China School of Computer Science and Technology Anhui University Hefei230601 China School of Artificial Intelligence Anhui University Hefei230601 China School of Computing Engineering and Mathematical Sciences La Trobe University Australia School of Information Engineering Guangdong University of Technology Guangzhou China

Understanding vehicles in images is important for various applications such as intelligent transportation and self-driving system. Existing vehicle-centric works typically pre-train models on large-scale classification datasets and then fine-tune them for specific downstream tasks. However, they neglect the specific characteristics of vehicle perception in different tasks and might thus lead to suboptimal performance. To address this issue, we propose a novel vehicle-centric pre-training framework called VehicleMAE, which incorporates the structural information including the spatial structure from vehicle profile information and the semantic structure from informative high-level natural language descriptions for effective masked vehicle appearance reconstruction. To be specific, we explicitly extract the sketch lines of vehicles as a form of the spatial structure to guide vehicle reconstruction. The more comprehensive knowledge distilled from the CLIP big model based on the similarity between the paired/unpaired vehicle image-text sample is further taken into consideration to help achieve a better understanding of vehicles. A large-scale dataset is built to pre-train our model, termed Autobot1M, which contains about 1M vehicle images and 12693 text information. Extensive experiments on four vehicle-based downstream tasks fully validated the effectiveness of our VehicleMAE. The source code and pre-trained models will be released at https://***/EventAHU/VehicleMAE. Copyright © 2023, The Authors. All rights reserved.

关键词： Large dataset

A Hybrid Method to Interest-informed and Mobility-aware Mobile Service Migration in Edge computing

学校读者我要写书评

暂无评论

A Hybrid Method to Interest-informed and Mobility-aware Mobi...

IEEE International Conference on Web Services (ICWS)

作者： Mengxuan Dai Yunni Xia Xu Wang Lei Yu Xingli Zhong Hui Liu Qing Xia QingLan Peng Xiaoning Sun Jiajun Su College of Computer Science Chongqing University Chongqing China College of Mechanical and Vehicle Chongqing University Chongqing China College of Computer Science Inner Mongolia University NeiMenggu China CISDI R & D co. Ltd Chongqing University Chongqing China School of Computer Science and Technology Beijing Institute of Technology Beijing China Chongqing Key Laboratory of Smart Electronics Reliability Technology Chongqing China School of Artificial Intelligence Henan University Zhengzhou China School of Computer and Information Science Chongqing Normal University Chongqing China Yunnan Key Laboratory of Service Computing Yunnan University of Finance and Economics Kunming China School of Digital Industry Jiangxi Normal University Shangrao China

ISBN: (数字)9798350368550

ISBN: (纸本)9798350368567

Mobile edge computing(MEC) is an innovative technology that deploys computing resources around the demand side to provide near-request and responsiveness-guaranteed computing and storage services. A major attention paid by related works in this direction is mobility, where mobile traces of both edge users and servers are analyzed and exploited for accommodating offloading and migration requests for computation resources in a highly dynamic MEC environment. Our research in this work suggests that information of user interests, in terms of points of interest (POI), can be exploited in conjunction with mobility as well and proposes a hybrid method for for interest-informed and mobility-aware service migration path selection(HIMS). It synthesizes a trajectory prediction model and user interests prediction one for selecting target servers and reliable service migration paths. Experimental results demonstrate that our approach outperforms traditional methods across multiple performance metrics, especially those with sole input of mobility.

关键词： Measurement Accuracy Web services Processor scheduling Computational modeling Predictive models Prediction algorithms User experience Trajectory Servers

Countering Eavesdroppers with Meta-learning-based Cooperative Ambient Backscatter Communications

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Chu, Nam H. Van Huynh, Nguyen Nguyen, Diep N. Hoang, Dinh Thai Gong, Shimin Shu, Tao Dutkiewicz, Eryk Phan, Khoa T. School of Electrical and Data Engineering University of Technology Sydney Australia School of Computing Engineering and the Built Environment Edinburgh Napier University Edinburgh United Kingdom School of Intelligent Systems Engineering Sun Yat-sen University Guangzhou China Department of Computer Science and Software Engineering Auburn University AuburnAL36849 United States School of Engineering and Mathematical Sciences Department of Computer Science and Information Technology La Trobe University Melbourne Australia

This article introduces a novel lightweight framework using ambient backscattering communications to counter eavesdroppers. In particular, our framework divides an original message into two parts. The first part, i.e., the active-transmit message, is transmitted by the transmitter using conventional RF signals. Simultaneously, the second part, i.e., the backscatter message, is transmitted by an ambient backscatter tag that backscatters upon the active signals emitted by the transmitter. Notably, the backscatter tag does not generate its own signal, making it difficult for an eavesdropper to detect the backscattered signals unless they have prior knowledge of the system. Here, we assume that without decoding/knowing the backscatter message, the eavesdropper is unable to decode the original message. Even in scenarios where the eavesdropper can capture both messages, reconstructing the original message is a complex task without understanding the intricacies of the message-splitting mechanism. A challenge in our proposed framework is to effectively decode the backscattered signals at the receiver, often accomplished using the maximum likelihood (MLK) approach. However, such a method may require a complex mathematical model together with perfect channel state information (CSI). To address this issue, we develop a novel deep meta-learning-based signal detector that can not only effectively decode the weak backscattered signals without requiring perfect CSI but also quickly adapt to a new wireless environment with very little knowledge. Simulation results show that our proposed learning approach, without requiring perfect CSI and complex mathematical model, can achieve a bit error ratio close to that of the MLK-based approach. They also clearly show the efficiency of the proposed approach in dealing with eavesdropping attacks and the lack of training data for deep learning models in practical scenarios. Copyright © 2023, The Authors. All rights reserved.

关键词： Backscattering

An Optimized Resource Scheduling Strategy for Hadoop Speculative Execution Based on Non-cooperative Game Schemes

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2020年第2期62卷 713-729页

作者： Yinghang Jiang Qi Liu Williams Dannah Dandan Jin Xiaodong Liu Mingxu Sun Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing210044China School of Computer and Software Nanjing University of Information Science&TechnologyNanjing210044China School of Computing Edinburgh Napier UniversityEdinburgh EH105DTUK School of Electrical Engineering University of JinanChinaand Centre for Health Sciences ResearchUniversity of SalfordSalfordGreater ManchesterM54WTUK

Hadoop is a well-known parallel computing system for distributed computing and large-scale data processes.“Straggling”tasks,however,have a serious impact on task allocation and scheduling in a Hadoop *** Execution(SE)is an efficient method of processing“Straggling”Tasks by monitoring real-time running status of tasks and then selectively backing up“Stragglers”in another node to increase the chance to complete the entire mission *** speculative execution strategies meet challenges on misjudgement of“Straggling”tasks and improper selection of backup nodes,which leads to inefficient implementation of speculative executive *** paper has proposed an Optimized Resource Scheduling strategy for Speculative Execution(ORSE)by introducing non-cooperative game *** ORSE transforms the resource scheduling of backup tasks into a multi-party non-cooperative game problem,where the tasks are regarded as game participants,whilst total task execution time of the entire cluster as the utility *** that case,the most benefit strategy can be implemented in each computing node when the game reaches a Nash equilibrium point,i.e.,the final resource scheduling scheme to be *** strategy has been implemented in *** results depict that the ORSE can maintain the efficiency of speculative executive processes and improve fault-tolerant and computation performance under the circumstances of Normal Load,Busy Load and Busy Load with Skewed Data.

关键词： Distributed computing speculative execution resource scheduling non-cooperative game theory