Cruise Missile Path Planning Based On Aco Algorithm And Bezier Curve Optimization,
2020
1. Dept. of Military Oceanography & Hydrography, Dalian Naval Academy, Dalian 116018, China;;
Cruise Missile Path Planning Based On Aco Algorithm And Bezier Curve Optimization, Shi Yan, Lihua Zhang, Shouquan Dong, Jue Wang
Journal of System Simulation
Abstract: For the low-altitude penetration of cruise missile, there is a large number of steering points and a larger steering angle in missile path planning based on ant colony algorithm. In order to solve this problem, a three-dimensional path planning method based on ant colony algorithm and Bezier curve optimization is proposed. The planning path node generated by ant colony algorithm was used as the control point to generate the flight path of Bezier curve, and then the curve was changed to be broken lines path. In order to avoid the unnavigable section, using the breadth first search algorithm to …
Research On Active Training Compliance Control Of Ankle Rehabilitation Robot,
2020
1. School of Mechatronics Engineering, Henan University of Science and Technology, Luoyang 471003, China;;2. Collaborative Innovation Center of Machinery Equipment Advanced Manufacturing, Henan Province, Henan University of Science and Technology, Luoyang 471003, China;
Research On Active Training Compliance Control Of Ankle Rehabilitation Robot, Yanbin Liu, Xiangyuan Pang, Yanbin Zhang, Bingjing Guo, Jianhai Han
Journal of System Simulation
Abstract: In order to ensure that ankle rehabilitation robot can accurately supply arbitrary characteristic training force for patient during active training, the pneumatic muscle redundant parallel driving ankle rehabilitation robot was taken as research objects, the zero error force tracking method and the compliance control strategy for active training were researched. The dynamics model of the ankle rehabilitation robot were set up, based on the impedance control theory, the trajectory planning method for the zero error force tracking was researched, and based on the Lyapunov’s stability theory, the pneumatic muscle redundant parallel driving compliance control strategy was proposed. Rehabilitation training …
Smart Routing: Towards Proactive Fault Handling Of Software-Defined Networks,
2020
Technological University Dublin
Smart Routing: Towards Proactive Fault Handling Of Software-Defined Networks, Ali Malik, Benjamin Aziz, Mo Adda, Chih-Heng Ke
Articles
In recent years, the emerging paradigm of software-defined networking has become a hot and thriving topic in both the industrial and academic sectors. Software-defined networking offers numerous benefits against legacy networking systems by simplifying the process of network management through reducing the cost of network configurations. Currently, data plane fault management is limited to two mechanisms: proactive and reactive. These fault management and recovery techniques are activated only after a failure occurrence and hence packet loss is highly likely to occur. This is due to convergence time where new network paths will need to be allocated in order to …
Novel Planar Wire-Grid Antenna Arrays For Automotive Radars Operating At 77 Ghz,
2020
The American University in Cairo
Novel Planar Wire-Grid Antenna Arrays For Automotive Radars Operating At 77 Ghz, Hossam Helaly
Theses and Dissertations
Automotive radars are the critical components for future driving assistance technologies. Nowadays, their usage is a constraint on the premium segment automobiles; however, there are intensive studies to facilitate these technologies to the lower segment. The main challenges that face automakers to develop new automotive radars are fabrication cost, compactness, bandwidth, and radiation properties. This research focuses on developing a novel class of planar antenna arrays, which operate at a frequency of 77 GHz. The proposed arrays can be fabricated using multilayered cheap printed circuit board lamination technology. The proposed antennas are arrayed using mixed wire-gridding and corporate arraying techniques, …
Investigating Patterns In Convolution Neural Network Parameters Using Probabilistic Support Vector Machines,
2020
Washington University in St. Louis
Investigating Patterns In Convolution Neural Network Parameters Using Probabilistic Support Vector Machines, Yuqiu Zhang
McKelvey School of Engineering Graduate Student Theses & Dissertations
Artificial neural networks(ANNs) are recognized as high-performance models for classification problems. They have proved to be efficient tools for many of today's applications like automatic driving, image and video recognition and restoration, big-data analysis. However, high performance deep neural networks have millions of parameters, and the iterative training procedure thus involves a very high computational cost. This research attempts to study the relationships between parameters in convolutional neural networks(CNNs). I assume there exists a certain relation between adjacent convolutional layers and proposed a machine learning model(MLM) that can be trained to represent this relation. The MLM's generalization ability is evaluated …
Ai-Assisted Network-Slicing Based Next-Generation Wireless Networks,
2020
University of Waterloo
Ai-Assisted Network-Slicing Based Next-Generation Wireless Networks, Xuemin Shen, Jie Gao, Wen Wu, Kangjia Lyu, Mushu Li, Weihua Zhuang, Xu Li, Jaya Rao
Electrical and Computer Engineering Faculty Research and Publications
The integration of communications with different scales, diverse radio access technologies, and various network resources renders next-generation wireless networks (NGWNs) highly heterogeneous and dynamic. Emerging use cases and applications, such as machine to machine communications, autonomous driving, and factory automation, have stringent requirements in terms of reliability, latency, throughput, and so on. Such requirements pose new challenges to architecture design, network management, and resource orchestration in NGWNs. Starting from illustrating these challenges, this paper aims at providing a good understanding of the overall architecture of NGWNs and three specific research problems under this architecture. First, we introduce a network-slicing based …
2-Visible Submodules And Fully 2-Visible Modules,
2020
Al Iraqia University
2-Visible Submodules And Fully 2-Visible Modules, Mahmood S. Fiadh, Wafaa H. Hanoon
Iraqi Journal for Computer Science and Mathematics
LetXbe aT-module, T is a commutative ring with identity andKbe a proper submodule ofX. In thispaper we introduce the concepts of 2-visible submodules and fully 2-visible modules as a generalizations of visiblesubmodules and fully visible modules resp., whereKis said to be 2-visible wheneverK=I2Kfor every nonzeroidealIofTand AT-moduleXis called fully 2-visible if for any proper submodule of it is 2-visible.Study some ofthe properties of these concepts also discuss the relationship 2-visible submodules and fully 2-visible modules with2-pure submoules and other related submodules and modules resp. are given
Critical Factors Affecting The Adoption Of Open Source Software Inpublic Organizations,
2020
Al Iraqia University
Critical Factors Affecting The Adoption Of Open Source Software Inpublic Organizations, Mohanad G. Yaseen, Saad A. Abd, Ibarhim Adeb
Iraqi Journal for Computer Science and Mathematics
Context:The way public organizations produce, acquire, use, and commercialize software ischanging as a result of open source software (OSS). Because of the numerous benefits provided by open sourcesoftware, public organizations began to use it to meet their demands. As a result, governments implement variousmeasures to encourage and facilitate OSS use. A variety of factors continue to influence the choice to implementOSS, which can have a positive or negative impact on the adoption process.Objective:The study’s purpose is to explore the most critical factors that may influence the open source softwareadoption process, which are drawn from chosen case studies from various domains …
A Brief Review Of Big Data Analytics Based On Machine Learning,
2020
Al Iraqia University
A Brief Review Of Big Data Analytics Based On Machine Learning, Ahmed Hussein Ali, Mahmood Zaki Abdullah, Shams N. Abdul-Wahab, Mohammad Al Sajri
Iraqi Journal for Computer Science and Mathematics
Owing to the exponential expansion in the data size, fast and efficient systems of analysis areextremely needed. The traditional algorithms of machine learning face the challenge of learning bottlenecks suchas; human participation, time, and the accuracy of prediction. But, the efficient and fast methods of dynamiclearning offer considerable advantages like lower human participation, rapid algorithms of learning, and easinessimplementation. This review paper presents the researches with a brief display for recently existing works in big dataanalytics and the effective algorithms of machine learning, furthermore, the issues of resources allocation in big data
Development Of Iot Based Hybrid Autonomous Network Robots (Anr),
2020
The American University in Cairo
Development Of Iot Based Hybrid Autonomous Network Robots (Anr), Chimsom Isidore Chukwuemeka
Theses and Dissertations
The integration of wireless sensor networks (WSNs) and multirobot systems (MRS) represents an active research area supporting a wide range of applications. This is because it enables ubiquitous applications due to the robots' mobility and detection capabilities associated with its deployment. These systems have many benefits, such as perception with extended coverage that facilitate wider exploration and surveillance, efficiency in data routing, effective and reliable task environment management, etc. However, integrating two fields of research means dealing with a range of challenges such as using effective architecture for WSNs and MRS, efficient communication protocols within a network of sensors nodes …
Dual-Axis Solar Tracker,
2020
Central Washington University
Dual-Axis Solar Tracker, Bryan Kennedy
All Undergraduate Projects
Renewable energies, and fuels that are not fossil fuel-based, are one of the prolific topics of debate in modern society. With climate change now becoming a primary focus for scientists and innovators of today, one of the areas for the largest amount of potential and growth is that of the capturing and utilization of Solar Energy. This method involves using a mechanical system to track the progression of the sun as it traverses the sky throughout the day. A dual-axis solar tracker such as the one designed and built for this project, can follow the sun both azimuthally and in …
How Facets Of Work Illuminate Sociotechnical Challenges Of Industry 5.0,
2020
University of San Francisco
How Facets Of Work Illuminate Sociotechnical Challenges Of Industry 5.0, Steven Alter
Business Analytics and Information Systems
This conceptual contribution explains how the idea of “facets of work” can refocus traditional sociotechnical concerns to increase their relevance in increasingly automated and digitalized workplaces far removed from situations studied by early sociotechnical researchers. A background section summarizes how the sociotechnical approach seems pervasive but possibly outdated in some ways. It explains how the idea of “facets of work” emerged from attempting to bring richer, more evocative ide-as to systems analysis and design. Focusing on facets of work during initial discussions of requirements could provide guidance without jumping prematurely to precision and notation needed for producing technical artifacts. Tables …
Exploring Pattern Mining Algorithms For Hashtag Retrieval Problem,
2020
University Of Science And Technology Houari Boumediene
Exploring Pattern Mining Algorithms For Hashtag Retrieval Problem, Asma Belhadi, Youcef Djenouri, Jerry Chun-Wei Lin, Chongsheng Zhang, Alberto Cano
Computer Science Publications
Hashtag is an iconic feature to retrieve the hot topics of discussion on Twitter or other social networks. This paper incorporates the pattern mining approaches to improve the accuracy of retrieving the relevant information and speeding up the search performance. A novel algorithm called PM-HR (Pattern Mining for Hashtag Retrieval) is designed to first transform the set of tweets into a transactional database by considering two different strategies (trivial and temporal). After that, the set of the relevant patterns is discovered, and then used as a knowledge-based system for finding the relevant tweets based on users' queries under the similarity …
College Of Computing And Engineering Graduate Catalog 2020-2021,
2020
Nova Southeastern University
College Of Computing And Engineering Graduate Catalog 2020-2021, Nova Southeastern University
College of Engineering and Computing Course Catalogs
No abstract provided.
Eyecom: An Innovative Approach For Computer Interaction,
2020
Marshall University
Eyecom: An Innovative Approach For Computer Interaction, Anam Mazhar
Theses, Dissertations and Capstones
The world is innovating rapidly, and there is a need for continuous interaction with the technology. Sadly, there do not exist promising options for paralyzed people to interact with the machines i.e., laptops, smartphones, and tabs. A few commercial solutions such as Google Glasses are costly and cannot be afforded by every paralyzed person for such interaction. Towards this end, the thesis proposes a retina-controlled device called EYECOM. The proposed device is constructed from off-the-shelf cost-effective yet robust IoT devices (i.e., Arduino microcontrollers, Xbee wireless sensors, IR diodes, and accelerometer). The device can easily be mounted on to the glasses; …
Load-Balancing Rendezvous Approach For Mobility-Enabled Adaptive Energy-Efficient Data Collection In Wsns,
2020
Nanjing University of Information Science & Technology
Load-Balancing Rendezvous Approach For Mobility-Enabled Adaptive Energy-Efficient Data Collection In Wsns, Jian Zhang, Jian Tang, Zhonghui Wang, Feng Wang, Gang Yu
Faculty and Student Publications
Copyright © 2020 KSII The tradeoff between energy conservation and traffic balancing is a dilemma problem in Wireless Sensor Networks (WSNs). By analyzing the intrinsic relationship between cluster properties and long distance transmission energy consumption, we characterize three node sets of the cluster as a theoretical foundation to enhance high performance of WSNs, and propose optimal solutions by introducing rendezvous and Mobile Elements (MEs) to optimize energy consumption for prolonging the lifetime of WSNs. First, we exploit an approximate method based on the transmission distance from the different node to an ME to select suboptimal Rendezvous Point (RP) on the …
Revisiting Lightweight Encryption For Iot Applications: Error Performance And Throughput In Wireless Fading Channels With And Without Coding,
2020
University of Jordan
Revisiting Lightweight Encryption For Iot Applications: Error Performance And Throughput In Wireless Fading Channels With And Without Coding, Yazid M. Khattabi, Mustafa M. Matalgah, Mohammed M. Olama
Faculty and Student Publications
© 2013 IEEE. Employing heavy conventional encryption algorithms in communications suffers from added overhead and processing time delay; and in wireless communications, in particular, suffers from severe performance deterioration (avalanche effect) due to fading. Consequently, a tremendous reduction in data throughput and increase in complexity and time delay may occur especially when information traverse resource-limited devices as in Internet-of-Things (IoT) applications. To overcome these drawbacks, efficient lightweight encryption algorithms have been recently proposed in literature. One of those, that is of particular interest, requires using conventional encryption only for the first block of data in a given frame being transmitted. …
Cooperative Relay Selection For Load Balancing With Mobility In Hierarchical Wsns: A Multi-Armed Bandit Approach,
2020
Nanjing University of Information Science & Technology
Cooperative Relay Selection For Load Balancing With Mobility In Hierarchical Wsns: A Multi-Armed Bandit Approach, Jian Zhang, Jian Tang, Feng Wang
Faculty and Student Publications
© 2013 IEEE. Energy efficiency is the major concern in hierarchical wireless sensor networks(WSNs), where the major energy consumption originates from radios for communication. Due to notable energy expenditure of long-range transmission for cluster members and data aggregation for Cluster Head (CH), saving and balancing energy consumption is a tricky challenge in WSNs. In this paper, we design a CH selection mechanism with a mobile sink (MS) while proposing relay selection algorithms with multi-user multi-armed bandit (UM-MAB) to solve the problem of energy efficiency. According to the definition of node density and residual energy, we propose a conception referred to …
Finding Data Races In Software Binaries With Symbolic Execution,
2020
Wright State University
Finding Data Races In Software Binaries With Symbolic Execution, Nathan D. Jackson
Browse all Theses and Dissertations
Modern software applications frequently make use of multithreading to utilize hardware resources better and promote application responsiveness. In these applications, threads share the program state, and synchronization mechanisms ensure proper ordering of accesses to the program state. When a developer fails to implement synchronization mechanisms, data races may occur. Finding data races in an automated way is an already challenging problem, but often impractical without source code or understanding how to execute the program under analysis. In this thesis, we propose a solution for finding data races on software binaries and present our prototype implementation BINRELAY. Our solution makes use …
Bimodal Emotion Classification Using Deep Learning,
2020
Technological University Dublin
Bimodal Emotion Classification Using Deep Learning, Ashutosh Kumar Singh
Dissertations
Multimodal Emotion Recognition is an emerging associative field in the area of Human Computer Interaction and Sentiment Analysis. It extracts information from each modality to predict the emotions accurately. In this research, Bimodal Emotion Recognition framework is developed with the decision-level fusion of Audio and Video modality using RAVDES dataset. Designing such frameworks are computationally expensive and require more time to train the network. Thus, a relatively small dataset has been used for the scope of this research. The conducted research is inspired by the use of neural networks for emotion classification from multimodal data. The developed framework further confirmed …
