Computer Engineering Commons^™

Low-Complexity Apit Algorithm And Its Opnet Simulation Of Underwater Acoustic Sensor Networks, Jiahui Xu, Keyu Chen, En Chen

Journal of System Simulation

Abstract: Due to the energy limitations of underwater acoustic sensor networks, low-complexity location algorithms are more suitable for underwater acoustic sensor networks. The traditional APIT algorithm can obtain better location accuracy with less control overhead, which is beneficial to the location of underwater sensor networks, but it has high complexity and large redundancy errors. This paper proposes a low-complexity APIT algorithm replaced the traditional grid SCAN algorithm with a point scanning method, and builds an underwater acoustic sensor network environment on the OPNET platform, and elaborates the implementation process of the location algorithm in underwater sensor network. Simulation results …

Study On Infrared Radiation Of Nmp Recovery System In Lithium Battery Pole Piece, Yanjun Xiao, Yang Huan, Yanping Kang

Journal of System Simulation

Abstract: The structure design of the NMP recovery system in the lithium battery pole piece coating process has many technology difficulties, including the vacuum and infrared radiation heating technology. For vacuum system, after the analysis of its impact on the coating process, and the drying needs of the NMP recovery system, through the analytic hierarchy process, the most suitable infrared radiation heater type can be determined. The process of recovering gaseous NMP is numerically simulated, and the simulation results of the system flow performance are obtained. The parameters of the drying time, arrangement mode and other parameters are determined by …

Research On The Mvc-Based Generation Of Test Paper And The Algorithm Of Subjective Criterion, Cuicui Zhang, Guoxiang Zhou, Yu Lei, Shi Lei, Qingqing Wang

Journal of System Simulation

Abstract: At home and abroad, the formed test system has a mature algorithm to the objective problem. However, there are still some problems in the subjective questioning. Therefore, it is feasible to design a MVC(Model View Controller) framework for the dynamic generation of papers, and to propose an automatic algorithm. In the paper volume generation system, the paper page is generated dynamically by the distributed view and the component loading technique. In the subjective automatic questioning algorithm, a bidirectional traversal space model algorithm is proposed, which uses the key words bidirectional matching and vector space model to calculate the answer …

Research On Evacuation Simulation Method Considering Social Behavior, Yuanyuan Deng, Liping Zheng, Ruiwen Cai

Journal of System Simulation

Abstract: In an emergency evacuation scenario, the typical social attributes of an individual impact their evacuation behavior. Two kinds of social factors, such as individual familiarity to the environment and the individual group, are introduced and applied in crowd evacuation simulation. An evacuation simulation method is proposed. The real-time collision avoidance technique of RVO library is used to simulate the dynamic motion of the population. The local target points and its selection mechanism are used to simulate the different social behaviors of the population. Experiments show that the familiarity to the environment and group factors have influence on the evacuation …

Research On Flexray Network Optimization Based On Switched Message Scheduling Algorithm, Yinan Xu, Xiangqi Kong, Mengzhuo Liu

Journal of System Simulation

Abstract: The development of vehicle electronic technology needs advanced in-vehicle communication network. Because of the high transmission speed, reliability and the flexible topology structure, the FlexRay network has become the most popular in-vehicle communication protocol in recent years. In order to meet the demand of network development, a scheduling algorithm based on switched FlexRay network was designed, and a new method that could calculate the Static segment and the worst case response time of Dynamic segment was put forward. The result of the simulation experiment shows that the transmission speed improves 26%, the slot number decreases by 44% and …

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, 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 …

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, …

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 …

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, 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 …

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

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, 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 …

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, 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, 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, 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, Nova Southeastern University

College of Engineering and Computing Course Catalogs

No abstract provided.

Brain Disease Detection From Eegs: Comparing Spiking And Recurrent Neural Networks For Non-Stationary Time Series Classification, Hristo Stoev

Dissertations

Modeling non-stationary time series data is a difficult problem area in AI, due to the fact that the statistical properties of the data change as the time series progresses. This complicates the classification of non-stationary time series, which is a method used in the detection of brain diseases from EEGs. Various techniques have been developed in the field of deep learning for tackling this problem, with recurrent neural networks (RNN) approaches utilising Long short-term memory (LSTM) architectures achieving a high degree of success. This study implements a new, spiking neural network-based approach to time series classification for the purpose of …

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, 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, 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, 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, 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, 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 …

Ensemble Lung Segmentation System Using Deep Neural Networks, Redha A. Ali, Russell C. Hardie, Hussin K. Ragb

Electrical and Computer Engineering Faculty Publications

Lung segmentation is a significant step in developing computer-aided diagnosis (CAD) using Chest Radiographs (CRs). CRs are used for diagnosis of the 2019 novel coronavirus disease (COVID-19), lung cancer, tuberculosis, and pneumonia. Hence, developing a Computer-Aided Detection (CAD) system would provide a second opinion to help radiologists in the reading process, increase objectivity, and reduce the workload. In this paper, we present the implementation of our ensemble deep learning model for lung segmentation. This model is based on the original DeepLabV3+, which is the extended model of DeepLabV3. Our model utilizes various architectures as a backbone of DeepLabV3+, such as …

Lm-Based Word Embeddings Improve Biomedical Named Entity Recognition: A Detailed Analysis, Liliya Akhtyamova, John Cardiff

Conference Papers

Recent studies have shown that contextualized word embeddings outperform other types of embeddings on a variety of tasks. However, there is little research done to evaluate their effectiveness in the biomedical domain under multi-task settings. We derive the contextualized word embeddings from the Flair framework and apply them to the task of biomedical NER on 5 benchmark datasets, yielding major improvements over the baseline and achieving competitive results over the current best systems. We analyze the sources of these improvements, reporting model performances over different combinations of word embeddings, and fine-tuning and casing modes.

Recent Developments In The General Atomic And Molecular Electronic Structure System, Guiseppe M.J. Barca, Colleen Bertoni, Laura Carrington, Dipayan Datta, Nuwan De Silva, J. Emillano Deustua, Dmitri G. Fedorov, Jeffrey R. Cour, Anastasia O. Gunina, Emilie Guidez, Taylor Harville, Stephan Irle, Joe Ivanic, Karol Kowalski, Sarom S. Leang, Wei Li, Jesse J. Lutz, Ilias Magoulas, Joani Mato, Vladimir Mironov, Hiroya Nakata, Buu Q. Pham, Piotr Piecuch, David Poole, Spencer R. Pruitt, Alistair P. Rendell, Luke B. Roskop, Klaus Ruedenberg, Tosaporn Sattasathuchana, Michael W. Schmidt, Jun Shen, Lyudmila Slipchenko, Masha Sosonkina, Vaibhav Sundriyal, Ananta Tiwari, Jorge L. Galvez Vallejo, Bryce Westheimer, Marta Włoch, Peng Xu, Federico Zahariev, Mark S. Gordon

Computational Modeling & Simulation Engineering Faculty Publications

A discussion of many of the recently implemented features of GAMESS (General Atomic and Molecular Electronic Structure System) and LibCChem (the C++ CPU/GPU library associated with GAMESS) is presented. These features include fragmentation methods such as the fragment molecular orbital, effective fragment potential and effective fragment molecular orbital methods, hybrid MPI/OpenMP approaches to Hartree-Fock, and resolution of the identity second order perturbation theory. Many new coupled cluster theory methods have been implemented in GAMESS, as have multiple levels of density functional/tight binding theory. The role of accelerators, especially graphical processing units, is discussed in the context of the new features …

Deformable Multisurface Segmentation Of The Spine For Orthopedic Surgery Planning And Simulation, Rabia Haq, Jérôme Schmid, Roderick Borgie, Joshua Cates, Michel Audette

Computational Modeling & Simulation Engineering Faculty Publications

Purpose: We describe a shape-aware multisurface simplex deformable model for the segmentation of healthy as well as pathological lumbar spine in medical image data.

Approach: This model provides an accurate and robust segmentation scheme for the identification of intervertebral disc pathologies to enable the minimally supervised planning and patient-specific simulation of spine surgery, in a manner that combines multisurface and shape statistics-based variants of the deformable simplex model. Statistical shape variation within the dataset has been captured by application of principal component analysis and incorporated during the segmentation process to refine results. In the case where shape statistics hinder detection …