检索结果-内蒙古大学图书馆

5th International Conference on Recent Developments in Science, engineering and Technology, REDSET 2019

作者： Arora, Vasudha Mongia, Shweta Department of Computer Science and Engineering GD Goenka University Gurugram India Department of Informatics UPES Dehradun India

ISBN: (纸本)9789811558290

The data used in cloud applications is directly exposed to the cloud service provider, and because of the potential compromise of the cloud, could also be learned by adversaries. When encrypted data is hosted on cloud provided that there are large amount of data files, utilization of encrypted data effectively becomes a very challenging task. In a cloud computing environment, where outsourced data of organizations is shared with a large number of users. These variety of users might be interested in retrieving certain specific data files during a given session. A popular and interesting way to do so is by using keyword-based search. These search techniques facilitate users to search and retrieve data files selectively in which the users are interested. These keyword-based searches are being widely used for plaintext searches. But data encryption poses a challenge to perform keyword search using existing paintext search methods to be used for encrypted outsourced data on cloud. In this paper, we have analyzed the searchable indexes that could be used to make a fast and effective search on encrypted outsourced data and proposed a scheme that could make fast and accurate searches over encrypted outsourced cloud data. Simulation results have revealed that the proposed scheme takes much less time in generating the searchable index as compared to already existing techniques. The vector space model being used earlier for keyword based searches on encrypted data, is relatively time consuming and hence leads to very high time complexity during relevance score calculations as well as index generation for large datasets. Hence the proposed scheme achieves a fast and secure relevance scoring for large number of datasets also and in much less time as compared to the vector space model. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Large dataset

来源：评论

学校读者我要写书评

暂无评论

On the Evaluation of Access-point Handovers for UAVs in Long-distance Missions

On the Evaluation of Access-point Handovers for UAVs in Long...

引用

2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021

作者： Fagundes, Leonardo A. Souza, Vitor Barbosa Brandao, Alexandre S. Núcleo de Especialização em Robótica Federal University of Viçosa Department of Electrical Engineering and Graduate Program on Computer Science Viçosa Brazil Federal University of Viçosa Graduate Program on Computer Science Department of Informatics Viçosa Brazil

ISBN: (纸本)9780738131153

Unmanned Aerial Vehicle (UAV) systems are being increasingly used in a broad range of applications requiring extensive communications either to interconnect the UAVs with each other or to connect them with Ground Control Stations (GCS). Due to the complexity and difficulty of performing long distance experiments with these robots, simulation becomes a viable and necessary alternative. However, focusing either on the modeling of UAV operations or communication dynamics, available simulation tools are not able to capture the complex interdependencies between these two aspects, especially in applications where extensive communications are required. The main contribution of this work is the modeling and implementation of strategies for enhancing connectivity of a UAV performing long-distance navigation tasks, taking into account applications' requirements. The proposed strategies aim at assessing the impact of frequent handovers between wireless access points in terms of packet loss and available bandwidth. The first strategy prioritizes maintaining a connection until the signal-to-noise ratio (SNR) observed by the robot reaches a predefined threshold. For this, it is assumed that the data to be transmitted is small enough so that the robot may change its modulation to obtain smaller bandwidths while improving connection time. The second one prioritizes bandwidth availability, thus, it always searches for a network that is able to offer data rates higher than a minimum threshold. A hybrid model is validated by considering the characteristics of each individual strategy. The capabilities of the simulation tool designed for this work are illustrated through some case-study scenarios. © 2021 IEEE.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

Adjusting Logit in Gaussian Form for Long-Tailed Visual Recognition

arXiv

引用

arXiv 2023年

作者： Li, Mengke Cheung, Yiu-Ming Lu, Yang Hu, Zhikai Lan, Weichao Huang, Hui Shenzhen China The Department of Computer Science Hong Kong Baptist University Hong Kong The Fujian Key Laboratory of Sensing and Computing for Smart City School of Informatics Xiamen University Xiamen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

It is not uncommon that real-world data are distributed with a long tail. For such data, the learning of deep neural networks becomes challenging because it is hard to classify tail classes correctly. In the literature, several existing methods have addressed this problem by reducing classifier bias, provided that the features obtained with long-tailed data are representative enough. However, we find that training directly on long-tailed data leads to uneven embedding space. That is, the embedding space of head classes severely compresses that of tail classes, which is not conducive to subsequent classifier learning. This paper therefore studies the problem of long-tailed visual recognition from the perspective of feature level. We introduce feature augmentation to balance the embedding distribution. The features of different classes are perturbed with varying amplitudes in Gaussian form. Based on these perturbed features, two novel logit adjustment methods are proposed to improve model performance at a modest computational overhead. Subsequently, the distorted embedding spaces of all classes can be calibrated. In such balanced-distributed embedding spaces, the biased classifier can be eliminated by simply retraining the classifier with class-balanced sampling data. Extensive experiments conducted on benchmark datasets demonstrate the superior performance of the proposed method over the state-of-the-art ones. Source code is available at https://***/Keke921/GCLLoss. Copyright © 2023, The Authors. All rights reserved.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Feature Fusion from Head to Tail for Long-Tailed Visual Recognition

arXiv

引用

arXiv 2023年

作者： Li, Mengke Hu, Zhikai Lu, Yang Lan, Weichao Cheung, Yiu-Ming Huang, Hui Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Department of Computer Science Hong Kong Baptist University Hong Kong Fujian Key Laboratory of Sensing and Computing for Smart City School of Informatics Xiamen University Xiamen China

The imbalanced distribution of long-tailed data presents a considerable challenge for deep learning models, as it causes them to prioritize the accurate classification of head classes but largely disregard tail classes. The biased decision boundary caused by inadequate semantic information in tail classes is one of the key factors contributing to their low recognition accuracy. To rectify this issue, we propose to augment tail classes by grafting the diverse semantic information from head classes, referred to as head-to-tail fusion (H2T). We replace a portion of feature maps from tail classes with those belonging to head classes. These fused features substantially enhance the diversity of tail classes. Both theoretical analysis and practical experimentation demonstrate that H2T can contribute to a more optimized solution for the decision boundary. We seamlessly integrate H2T in the classifier adjustment stage, making it a plug-and-play module. Its simplicity and ease of implementation allow for smooth integration with existing long-tailed recognition methods, facilitating a further performance boost. Extensive experiments on various long-tailed benchmarks demonstrate the effectiveness of the proposed H2T. The source code is available at https://***/Keke921/H2T. Copyright © 2023, The Authors. All rights reserved.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Exploiting optimum acoustic features in COVID-19 individual's breathing sounds

Exploiting optimum acoustic features in COVID-19 individual'...

引用

2021 International Research Conference on Smart Computing and Systems engineering, SCSE 2021

作者： Milani, M. G. Manisha Ramashini, Murugaiya Murugiah, Krishani Chamal, Lanka Geeganage Shamaan Universiti Brunei Darussalam Faculty of Integrated Technologies Brunei Brunei Uva Wellassa University Department of Computer Science and Informatics Sri Lanka Pavendar Bharathidasan College of Engineering and Technology Department of Biotechnology India School of Engineering Sri Lanka Technological Campus Sri Lanka

ISBN: (纸本)9781665409650

The world is facing an extreme crisis due to the COVID-19 pandemic. The COVID-19 virus interrupts the world's economy and social factors;thus, many countries fall into poverty. Also, they lack expertise in this field and could not make an effort to perform the necessary polymerase chain reaction (PCR) or other expensive laboratory tests. Therefore, it is important to find an alternative solution to the early prediction of COVID-19 infected persons with a low-cost method. The objective of this study is to detect COVID-19 infected individuals through their breathing sounds. To perform this task, twenty-two (22) acoustic features are extracted. The optimum features in each COVID-19 infected breathing sound is identified among these features through a feature engineering method. This proposed feature engineering method is a hybrid model that includes;statistical feature evaluation, PCA, and k-mean clustering techniques. The final results of this proposed Optimum Acoustic Feature engineering (OAFE) model show that breathing sound signals' Kurtosis feature is more effective in distinguishing COVID-19 infected individuals from healthy individuals. © 2021 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Various Modulation Types Classification on the Air by Convolutional Neural Network 23

Various Modulation Types Classification on the Air by Convol...

引用

Proceedings of the 7th International Conference on Future Networks and Distributed Systems

作者： Yousif I Hammadi Mokhalad Abdulameer Kadhim Alsaeedi Omar Abdulkareem Mahmood Aws Zuhair Sameen Mohammed Saleh Ali Muthanna Ahmed Aziz Ammar Muthanna Dep. of Medical Instruments Engineering Techniques Bilad Alrafidain University College Iraq Department of Communications Engineering University of Diyala Iraq Department of Medical Instrumentation Engineering Techniques Al-Farahidi University Iraq Institute of Computer Technologies and Information Security Southern Federal University Russia Department of computer science Benha university Egypt and International Business Management Department Tashkent State University of Economics Uzbekistan Department of Telecommunication Networks and Data Transmission The Bonch Bruevich Saint Petersburg State University of Telecommunications Russia and Department of Applied Probability and Informatics Peoples Friendship University of Russia Russia

ISBN: (纸本)9798400709036

Deep learning (DL), a relatively recent AI technique, has been successfully applied to the problem of automated modulation categorization (AMC), with promising results. An essential part of developing the spectrum-sensing capabilities needed by software-defined radio is carrying out radio signal classification jobs, which we did in this research by introducing a better deep neural architecture. Different detection techniques were utilized in the literature; however, DL neural networks are recently utilized in this field. Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM) which is one variation of the RNN network, and other techniques are some of the employed DL architectures in the field of AMC. In this paper, Convolutional Neural Network (CNN) model has been built to automatically classify ten-modulation formats correctly. The suggested CNN network is constructed mainly of six-Convolutional layers. The overall number of trainable parameters in the proposed network is 1,757,962. Thus, the network accuracy, which was achieved during the training reached more than 90%. Python programming packages have been used to implement the suggested approach using *** platform, which provides wide-range of facilities.

关键词：

来源：评论

学校读者我要写书评

暂无评论

COVID19 Impact on Medical Clinics, Analysing and Devising a Safety Software Model for Clinics 4

COVID19 Impact on Medical Clinics, Analysing and Devising a ...

引用

4th International Conference on Computing, Electronics and Communications engineering, iCCECE 2021

作者： Fetaji, Majlinda Fetaji, Bekim Aliu, Azir Snopce, Halil Zeqiri, Izet Ebibi, Mirlanda Ali, Maaruf South East European University Faculty of Computer Sciences Tetovo Macedonia Mother Teresa University Faculty of Informatics Skopje Macedonia Faculty of Economy South East European University Tetovo Albania Epoka University Department of Computer Engineering Tirana Albania

ISBN: (纸本)9781665449113

The focus of this research is on investigating and identifying what constitutes a safe software model of a medical clinic that will enable and enhance its protection for healthcare providers and its patients by devising a model of a software system. There is a gap in the published research regarding the understanding of impacting factors of COVID19 in the safe functioning of a medical clinic. This Case Study investigated several impacting factors. The aims of this research project are: increasing the safety effectiveness of both the hospital personnel and patients. Next, to solve the problems with tracking the illnesses of patients, a more rigorous database indexing system was implemented with data provenance. With this technique in the database, it kept track of illnesses (when, why, in whom did it appear or any kind of other developments), login details (when, who is logged in, logged out), which is more important especially for medical systems. Also, which doctors interacted with the patients (what drug have been administered, their performance, percentage of efficacy, successfully or unsuccessfully) and other data mining information. Because this project is envisioned to be continually supported, it should evolve and deal with the problems encountered in modern hospitals. The system has been evaluated on its functionalities and the safety usability, on two groups of users: Those with a computer science background and those from a different field. Afterwards regression analyses were used to determine the impact. The research study contributed with identified impacting factors for such systems, analyses of the improvement in conceptual increase of safety and usability. Insights and recommendations are provided. © 2021 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Effective Searching for the Honeybee Queen in a Living Colony

Effective Searching for the Honeybee Queen in a Living Colon...

引用

IEEE International Conference on Automation Science and engineering (CASE)

作者： Jan Blaha Jan Mikula Tomáš Vintr Jiří Janota Jiří Ulrich Tomáš Rouček Fatemeh Rekabi-Bana Laurenz Alexander Fedotoff Martin Stefanec Thomas Schmickl Farshad Arvin Miroslav Kulich Tomáš Krajník Faculty of Electrical Engineering Czech Technical University in Prague Czechia Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Czechia Computer Science Department Durham University United Kingdom Department of Zoology Artificial Life Lab Institute of Biology University of Graz Graz Austria

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Despite the importance of honeybees as pollinators for the entire ecosystem and their recent decline threatening agricultural production, the dynamics of the living colony are not well understood. In our EU H2020 RoboRoyale project, we aim to support the pollination activity of the honeybees through robots interacting with the core element of the honeybee colony, the honeybee queen. In order to achieve that, we need to understand how the honeybee queen behaves and interacts with the surrounding worker bees. To gather the necessary data, we observe the queen with a moving camera, and occasionally, we instruct the system to perform selective observations elsewhere. In this paper, we deal with the problem of searching for the honeybee queen inside a living colony. We demonstrate that combining spatio-temporal models of queen presence with efficient search methods significantly decreases the time required to find her. This will minimize the chance of missing interesting data on the infrequent behaviors or queen-worker interactions, leading to a better understanding of the queen’s behavior over time. Moreover, a faster search for the queen allows the robot to leave her more frequently and gather more data in other areas of the honeybee colony.

关键词： computer aided software engineering Automation Biological system modeling Ecosystems Robot vision systems Production Search problems Cameras Path planning Robots

来源：评论

学校读者我要写书评

暂无评论

Toward Perpetual Occlusion-Aware Observation of Comb States in Living Honeybee Colonies

Toward Perpetual Occlusion-Aware Observation of Comb States ...

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Jan Blaha Tomáš Vintr Jan Mikula Jiří Janota Tomáš Rouĉek Jiří Ulrich Fatemeh Rekabi-Bana Laurenz Alexander Fedotoff Martin Stefanec Thomas Schmickl Farshad Arvin Miroslav Kulich Tomáš Krajník Faculty of Electrical Engineering Czech Technical University in Prague Czechia Computer Science Department Durham University United Kingdom Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Czechia Department of Zoology Artificial Life Lab Institute of Biology University of Graz Graz Austria

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Honeybees are one of the most important pollinators in the ecosystem. Unfortunately, the dynamics of living honeybee colonies are not well understood due to their complexity and difficulty of observation. In our project “RoboRoyale”, we build and operate a robot to be a part of a bio-hybrid system, which currently observes the honeybee queen in the colony and physically tracks it with a camera. Apart from tracking and observing the queen, the system needs to monitor the state of the honeybee comb which is most of the time occluded by workerbees. This introduces a necessary tradeoff between tracking the queen and visiting the rest of the hive to create a daily map. We aim to collect the necessary data more effectively. We evaluate several mapping methods that consider the previous observations and forecasted densities of bees occluding the view. To predict the presence of bees, we use previously established maps of dynamics developed for autonomy in human-populated environments. Using data from the last observational season, we show significant improvement of the informed comb mapping methods over our current system. This will allow us to use our resources more effectively in the upcoming season.

关键词： Biological system modeling Robot vision systems Ecosystems Data collection Cameras Data models Complexity theory Biomedical monitoring Monitoring Intelligent robots

来源：评论

学校读者我要写书评

暂无评论

Optimal One- and Two-Sided Multi-level ASK Modulation or RIS-Assisted Noncoherent Communication Systems

arXiv

引用

arXiv 2024年

作者： Mukhopadhyay, Srijika Reddy, Badri Ramanjaneya Dash, Soumya P. Alexandropoulos, George C. Aïssa, Sonia The School of Electrical Sciences Indian Institute of Technology Bhubaneswar Khordha Argul India The Department of Informatics and Telecommunications National and Kapodistrian University of Athens Panepistimiopolis Ilissia Athens15784 Greece The Department of Electrical and Computer Engineering University of Illinois ChicagoIL60601 United States MontrealQC Canada

In this paper, we analyze the performance of one- and two-sided amplitude shift keying (ASK) modulations in single-input single-output wireless communication aided by a reconfigurable intelligent surface (RIS). Two scenarios are considered for the channel conditions: a blocked direct channel between the transmitter and the receiver, and an unblocked one. For the receiver, a noncoherent maximum likelihood detector is proposed, which detects the transmitted data signal based on statistical knowledge of the channel. The system’s performance is then evaluated by deriving the symbol error probability (SEP) for both scenarios using the proposed noncoherent receiver structures. We also present a novel optimization framework to obtain the optimal one- and two-sided ASK modulation schemes that minimize the SEP under constraints on the available average transmit power for both the blocked and unblocked direct channel scenarios. Our extensive numerical investigations showcase that the considered RIS-aided communication system achieves superior error performance with both derived SEP-optimal ASK modulation schemes as compared to respective traditional ASK modulation. It is also demonstrated that, between the two proposed modulation schemes, the two-sided one yields the best SEP. The error performance is further analyzed for different system parameters, providing a comprehensive performance investigation of RIS-assisted noncoherent wireless communication systems. © 2024, CC BY.

关键词： Amplitude shift keying

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：