检索结果-内蒙古大学图书馆

Multidisciplinary engineering and Applied science (ICMEAS), International Conference on

作者： Emmanuel Alozie Nasir Faruk Abubakar Abdulkarim Aliyu D. Usman Yusuf Olayinka Imam-Fulani Salisu Garba Kayode S. Adewole Abdulkarim A. Oloyede Olugbenga A. Sowande Bashir Abdullahi Baba Abdulwaheed Musa Agbotiname Lucky Imoize Yinusa A. Adediran Hawau I. Olagunju Lawan S. Taura Department of Information Technology Sule Lamido University Kafin Hausa Nigeria Directorate of Information and Communication Technology Sule Lamido University Kafin Hausa Nigeria Department of Electrical Engineering Ahmadu Bello University Nigeria Department of Electrical and Telecommunications Engineering Kampala International University Kansanga Kampala Uganda Department of Electronics and Telecommunication Engineering Ahmadu Bello University Nigeria Department of Telecommunication Science University of Ilorin Ilorin Nigeria Department of Software Engineering Sule Lamido University Kafin Hausa Nigeria Department of Computer Science University of Ilorin Ilorin Nigeria Department of Cyber Security Sule Lamido University Kafin Hausa Nigeria Department of Electrical and Computer Engineering Kwara State University Malete Nigeria Institute for Intelligent Systems University of Johannesburg Johannesburg South Africa Department of Electrical and Electronics Engineering University of Lagos Akoka Lagos Nigeria Department of Electrical Engineering and Information Technology Institute of Digital Communication Ruhr University Bochum Germany Department of Electrical and Electronics Engineering University of Ilorin Ilorin Nigeria Department of Physics Sule Lamido University Kafin Hausa Nigeria

Signal propagation in a particular region differs from another due to differences in atmospheric, climatic and environmental properties, distinct terrain and clutter features. Adequate analysis is essential to understand the radio propagation behavior in a particular region. The ITU-R designated four rain regions, M, N, P, and Q, for Nigeria representing the rain rate distribution and also provided further classifications based on ground conductivity, among other salient parameters. Based on these classifications, this paper utilized the EDX Signal Pro software® to model and simulate a typical Point-to-Point (P2P), Non-Line of Sight (NLOS) link scenarios for 5G networks. The objective was to estimate and compare the total loss, excess loss, and flat fade margins for each rain region in Nigeria. Results obtained from the comparison showed that signals propagating in region N experience the highest level of losses and fading, while, region Q has the least losses and fading.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Algorithmic Framework for Analyzing and Simulating Multi-Axial Robotic Transformations in Spatial Coordinates

Algorithmic Framework for Analyzing and Simulating Multi-Axi...

引用

IEEE International Conference on Robotic Computing (IRC)

作者： Andrew O. Benyeogor Tobore L. Igbigbi Mbadiwe S. Benyeogor Abubakar A. Dahiru Prosper Agumey Ekarika B. Uwak CTE - Computer Science & Robotics Lab. International Leadership of Texas Aggieland Texas USA Dept. Business Information Systems Central Michigan University Mount Pleasant Michigan USA Institute of Physics University of Münster Münster Germany National Information Technology Development Agency (NITDA) Abuja - FCT Nigeria Industrial Liaison Directorate Accra Technical University Accra Ghana Dept. Physics & Physics Engineering Obafemi Awolowo University Ile-Ife Osun State Nigeria

This paper describes the mathematical background, derivation, and application of homogeneous transformation matrices for robotics, as well as algorithms and simulations demonstrating their utility. It shows how to obtain any arbitrary rotation matrix by combining rotations around multiple axes. The resulting generalized rotation matrix is used to obtain a 3x3 rotation matrix that depends on the angles of rotation about the x, y, and z-axes. We also derived the generic homogeneous transformation matrix, which combines the rotation matrix with a translation vector to represent a transformation in 3D space. The resulting 4x4 transformation matrix is used to convert coordinates between different frame-of-reference in a simulated robotic workspace. The algorithm was used to simulate the trans-rotation of kinematic chains in robotics, based on the derived transformation matrix, thus demonstrating the correctness of the underlying models.

关键词：

来源：评论

学校读者我要写书评

暂无评论

BOSS: BIDIRECTIONAL ONE-SHOT SYNTHESIS OF ADVERSARIAL EXAMPLES

arXiv

引用

arXiv 2021年

作者： Alkhouri, Ismail R. Velasquez, Alvaro Atia, George K. Department of Electrical and Computer Engineering University of Central Florida OrlandoFL United States Information Directorate Air Force Research Laboratory RomeNY United States Department of Computer Science University of Central Florida OrlandoFL United States

The design of additive perturbations to the inputs of classifiers has become a central focus of adversarial machine learning. An alternative approach is to synthesize adversarial examples using structures akin to generative adversarial networks, albeit with the use of large amounts of training data. By contrast, this paper considers the one-shot synthesis of adversarial examples that requires only a single reference datum. In particular, we explore solutions where the generated data must simultaneously satisfy user-defined constraints on its structural similarity to the reference input datum and the output of the classifier of interest it induces. This gives rise to what we call the Bidirectional One-Shot Synthesis (BOSS) problem. We prove that the BOSS problem is NP-complete. The experimental results verify that the targeted and confidence reduction attack methods developed either outperform or on par with state-of-the-art methods. © 2021, CC BY.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

An extensive study of sentiment analysis techniques: A survey

引用

AIP Conference Proceedings 2023年 030022页

作者： Lafta Raheem Ali Bassam Noori Shaker Sabah Abdulazeez Jebur General Directorate of Education of Salahuddin Governorate Salahuddin Iraq Computer Science Department College of Computer Science and Information Technology University of Al-Qadisiyah Al Diwaniyah Iraq Department of Computer Techniques Engineering Imam Al-Kadhum College Baghdad Iraq

Text mining is one of Artificial Intelligent (AI) technologies that uses Natural Language Processing (NLP) for extracting data from structured text. Sentiment analysis (also known as opinion mining) is one of text mining techniques, which is the computational study of personals' behaviours and opinions. The importance of sentiment analysis increases extensively with the enormous growth of the internet sites such as e-commerce, blogs, social media sites, etc. The aim of the survey is to give full view about the most important sentiment analysis techniques. The paper also represents a major contribution through categorizing the SA techniques in an easy and helpful manner for any researcher through classifying SA based on three essential approaches; machine learning-based, lexicon-based, and hybrid approach. Each approach may contain sub-divisions which in turn represent the techniques of SA classification.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Smart Healthcare System for Severity Prediction and Critical Tasks Management of COVID-19 Patients in IoT-Fog Computing Environments

引用

Computational Intelligence and Neuroscience 2022年第0期2022卷 5012962页

作者： Hameed Abdulkareem, Karrar Awad Mutlag, Ammar Musa Dinar, Ahmed Frnda, Jaroslav Abed Mohammed, Mazin Hasan Zayr, Fawzi Lakhan, Abdullah Kadry, Seifedine Ali Khattak, Hasan Nedoma, Jan College of Agriculture Al-Muthanna University Samawah66001 Iraq College of Engineering University of Warith Al-Anbiyaa Karbala Iraq Ministry of Education General Directorate of Curricula Pure Science Department Baghdad Iraq Engineering Department University of Technology- Iraq Baghdad Iraq Department of Quantitative Methods and Economic Informatics Faculty of Operation and Economics of Transport and Communication University of Žilina Žilina Slovakia Department of Telecommunications Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava Poruba Ostrava Czech Republic College of Computer Science and Information Technology University of Anbar 11 Ramadi Anbar Iraq Department of Biochemistry College of Medicine University of Wasit Wasit Iraq Department of Computer Science and Artificial Intelligence Wenzhou University Wenzhou325035 China Noroff University College Kristiansand Norway Islamabad44500 Pakistan

COVID-19 has depleted healthcare systems around the world. Extreme conditions must be defined as soon as possible so that services and treatment can be deployed and intensified. Many biomarkers are being investigated in order to track the patient's condition. Unfortunately, this may interfere with the symptoms of other diseases, making it more difficult for a specialist to diagnose or predict the severity level of the case. This research develops a Smart Healthcare System for Severity Prediction and Critical Tasks Management (SHSSP-CTM) for COVID-19 patients. On the one hand, a machine learning (ML) model is projected to predict the severity of COVID-19 disease. On the other hand, a multi-agent system is proposed to prioritize patients according to the seriousness of the COVID-19 condition and then provide complete network management from the edge to the cloud. Clinical data, including Internet of Medical Things (IoMT) sensors and Electronic Health Record (EHR) data of 78 patients from one hospital in the Wasit Governorate, Iraq, were used in this study. Different data sources are fused to generate new feature pattern. Also, data mining techniques such as normalization and feature selection are applied. Two models, specifically logistic regression (LR) and random forest (RF), are used as baseline severity predictive models. A multi-agent algorithm (MAA), consisting of a personal agent (PA) and fog node agent (FNA), is used to control the prioritization process of COVID-19 patients. The highest prediction result is achieved based on data fusion and selected features, where all examined classifiers observe a significant increase in accuracy. Furthermore, compared with state-of-the-art methods, the RF model showed a high and balanced prediction performance with 86% accuracy, 85.7% F-score, 87.2% precision, and 86% recall. In addition, as compared to the cloud, the MAA showed very significant performance where the resource usage was 66% in the proposed model and 34% in

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Investigation of the Impact of Height and Bandwidth on Path Loss Exponent of 5G FR1 Wireless Networks at 800, 3500, and 5900 MHz

Investigation of the Impact of Height and Bandwidth on Path ...

引用

Multidisciplinary engineering and Applied science (ICMEAS), International Conference on

作者： Yusuf Olayinka Imam-Fulani Nasir Faruk Aliyu D. Usman Abubakar Abdulkarim Abdoulie M.S Tekanyi Abdulmalik S. Yaro Emmanuel Alozie Salisu Garba Kayode S. Adewole Abdulkarim A. Oloyede Olugbenga A. Sowande Bashir Abdullahi Baba Abdulwaheed Musa Agbotiname Lucky Imoize Yinusa A. Adediran Hawau I. Olagunju Lawan S. Taura Department of Telecommunication Science University of Ilorin Ilorin Nigeria Department of Electronics and Telecommunication Engineering Ahmadu Bello University Zaria Nigeria Department of Information Technology Sule Lamido University Kafin Hausa Nigeria Directorate of Information and Communication Technology Sule Lamido University Kafin Hausa Nigeria Department of Electrical Engineering Ahmadu Bello University Zaria Nigeria Department of Electrical and Telecommunication Engineering Kampala International University Kampala Uganda Department of Informatics and Qualitative Methods Faculty of Informatics and Management University of Hradec Králové Hradec Králové Czech Republic Department of Software Engineering Sule Lamido University Kafin Hausa Nigeria Department of Computer Science University of Ilorin Ilorin Nigeria Department of Electrical and Computer Engineering Kwara State University Malete Nigeria Institute for Intelligent Systems University of Johannesburg Johannesburg South Africa Department of Electrical and Electronics Engineering University of Lagos Lagos Nigeria Department of Electrical Engineering and Information Technology Institute of Digital Communication Ruhr University Bochum Germany Department of Electrical and Electronics Engineering University of Ilorin Ilorin Nigeria Department of Physics Sule Lamido University Kafin Hausa Nigeria

5G communication systems provide an end-to-end wireless connection to billions of users and devices across the globe. The quality of signals received during radio communication is notably influenced by the behavior of the radio propagation channel. A major parameter used in characterizing this channel is the Path Loss Exponent (PLE). Several works that have estimated and analyzed the PLE mostly considered the effect of distance and carrier frequency. However, the effect of base station antenna height and channel bandwidth on the PLE for 5G networks have not been adequately considered. To address this, the impact of antenna height of base station and channel bandwidth on the PLE within the 5G Frequency Range 1 (FR1) frequencies was investigated in this study, specifically at 800, 3500, and 5900 MHz. The licensed EDX Signal Pro software® with Cirrus high resolution global terrain and clutter data base was utilized to model, simulate and analyze the PLE for Kano City, Nigeria. Results showed that for the tested frequencies, an increase in either base station height or channel bandwidth leads to a significant reduction in the PLE. This study can be utilized by network planning engineers and the wireless research community to further improve network implementation and optimization toward understanding the behavior of signal propagation in 5G networks and beyond.

关键词：

来源：评论

学校读者我要写书评

暂无评论

ANDiE the Autonomous Neutron Diffraction Explorer

引用

Neutron News 2023年第2期34卷 6-7页

作者： Austin McDannald Matthias Frontzek Andrei T. Savici Mathieu Doucet Efrain E. Rodriguez Kate Meuse Jessica Opsahl-Ong Daniel Samarov Ichiro Takeuchi William Ratcliff A. Gilad Kusne 1 Materials Measurement Laboratory NIST Gaithersburg Maryland USA 2 Neutron Sciences Directorate ORNL Oak Ridge Tennessee USA 3 Department of Chemistry and Biochemistry University of Maryland College Park Maryland USA4 Maryland Quantum Materials Center College Park Maryland USA 5 Department of Computer Science Cornell University Ithaca New York USA 6 Department of Computer Science Rice University Houston Texas USA 7 Information Technology Laboratory NIST Gaithersburg Maryland USA 4 Maryland Quantum Materials Center College Park Maryland USA8 Department of Materials Science and Engineering University of Maryland College Park Maryland USA 8 Department of Materials Science and Engineering University of Maryland College Park Maryland USA9 NIST Center for Neutron Research NIST Gaithersburg Maryland USA 1 Materials Measurement Laboratory NIST Gaithersburg Maryland USA8 Department of Materials Science and Engineering University of Maryland College Park Maryland USA

来源：评论

学校读者我要写书评

暂无评论

Target Defense against Sequentially Arriving Intruders

arXiv

引用

arXiv 2022年

作者： Pourghorban, Arman Dorothy, Michael Shishika, Daigo Von Moll, Alexander Maity, Dipankar The Department of Electrical and Computer Engineering The University of North Carolina CharlotteNC28223 United States The Computational and Information Sciences Directorate Army Research Laboratory APG MD20783 United States The Mechanical Engineering Department George Mason University FairfaxVA22030 United States Control Science Center Air Force Research Laboratory WPAFB OH45433 United States

We consider a variant of the target defense problem where a single defender is tasked to capture a sequence of incoming intruders. The intruders’ objective is to breach the target boundary without being captured by the defender. As soon as the current intruder breaches the target or gets captured by the defender, the next intruder appears at a random location on a fixed circle surrounding the target. Therefore, the defender’s final location at the end of the current game becomes its initial location for the next game. Thus, the players pick strategies that are advantageous for the current as well as for the future games. Depending on the information available to the players, each game is divided into two phases: partial information and full information phase. Under some assumptions on the sensing and speed capabilities, we analyze the agents’ strategies in both phases. We derive equilibrium strategies for both the players to optimize the capture percentage using the notions of engagement surface and capture circle. We quantify the percentage of capture for both finite and infinite sequences of incoming intruders. © 2022, CC BY.

关键词： Location

来源：评论

学校读者我要写书评

暂无评论

Toward Efficient Online Scheduling for Distributed Machine Learning Systems

arXiv

引用

arXiv 2021年

作者： Yu, Menglu Liu, Jia Wu, Chuan Ji, Bo Bentley, Elizabeth S. Department of Computer Science Iowa State University AmesIA50011 United States Department of Electrical and Computer Engineering The Ohio State University ColumbusOH43210 United States Department of Computer Science Virginia Tech BlacksburgVA24061 United States Department of Computer Science The University of Hong Kong Hong Kong Air Force Research Laboratory Information Directorate RomeNY13441 United States

Recent years have witnessed a rapid growth of distributed machine learning (ML) frameworks, which exploit the massive parallelism of computing clusters to expedite ML training. However, the proliferation of distributed ML frameworks also introduces many unique technical challenges in computing system design and optimization. In a networked computing cluster that supports a large number of training jobs, a key question is how to design efficient scheduling algorithms to allocate workers and parameter servers across different machines to minimize the overall training time. Toward this end, in this paper, we develop an online scheduling algorithm that jointly optimizes resource allocation and locality decisions. Our main contributions are three-fold: i) We develop a new analytical model that considers both resource allocation and locality;ii) Based on an equivalent reformulation and observations on the worker-parameter server locality configurations, we transform the problem into a mixed packing and covering integer program, which enables approximation algorithm design;iii) We propose a meticulously designed approximation algorithm based on randomized rounding and rigorously analyze its performance. Collectively, our results contribute to the state of the art of distributed ML system optimization and algorithm design. © 2021, CC BY.

关键词： Approximation algorithms

来源：评论

学校读者我要写书评

暂无评论

Apple: Adaptive planner parameter learning from evaluative feedback

arXiv

引用

arXiv 2021年

作者： Wang, Zizhao Xiao, Xuesu Warnell, Garrett Stone, Peter Department of Electrical and Computer Engineering University of Texas at Austin AustinTX78712 United States Department of Computer Science University of Texas at Austin AustinTX78712 United States Computational and Information Sciences Directorate Army Research Laboratory AustinTX78712 United States Sony AI

Classical autonomous navigation systems can control robots in a collision-free manner, oftentimes with verifiable safety and explainability. When facing new environments, however, fine-tuning of the system parameters by an expert is typically required before the system can navigate as expected. To alleviate this requirement, the recently-proposed Adaptive Planner Parameter Learning paradigm allows robots to learn how to dynamically adjust planner parameters using a teleoperated demonstration or corrective interventions from non-expert users. However, these interaction modalities require users to take full control of the moving robot, which requires the users to be familiar with robot teleoperation. As an alternative, we introduce APPLE, Adaptive Planner Parameter Learning from Evaluative Feedback (real-time, scalar-valued assessments of behavior), which represents a less-demanding modality of interaction. Simulated and physical experiments show APPLE can achieve better performance compared to the planner with static default parameters and even yield improvement over learned parameters from richer interaction modalities. Copyright © 2021, The Authors. All rights reserved.

关键词： Fruits

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：