Computer Engineering Commons^™

Design And Control Of A Tunable-Stiffness Coiled-Spring Actuator, Shivangi Misra, Mason Mitchell, Rongqian Chen, Cynthia Sung

Lab Papers (GRASP)

We propose a novel design for a lightweight and compact tunable stiffness actuator capable of stiffness changes up to 20x. The design is based on the concept of a coiled spring, where changes in the number of layers in the spring change the bulk stiffness in a near-linear fashion. We present an elastica nested rings model for the deformation of the proposed actuator and empirically verify that the designed stiffness-changing spring abides by this model. Using the resulting model, we design a physical prototype of the tunable-stiffness coiled-spring actuator and discuss the effect of design choices on the resulting achievable …

Leveraging Aruco Fiducial Marker System For Bridge Displacement Estimation Using Unmanned Aerial Vehicles, Mohamed Aly

Computer Science and Engineering: Theses, Dissertations, and Student Research

The use of unmanned aerial vehicles (UAVs) in construction sites has been widely growing for surveying and inspection purposes. Their mobility and agility have enabled engineers to use UAVs in Structural Health Monitoring (SHM) applications to overcome the limitations of traditional approaches that require labor-intensive installation, extended time, and long-term maintenance. One of the critical applications of SHM is measuring bridge deflections during the bridge operation period. Due to the complex remote sites of bridges, remote sensing techniques, such as camera-equipped drones, can facilitate measuring bridge deflections. This work takes a step to build a pipeline using the state-of-the-art computer …

Game Based Learning: Engaging Students And Measuring Their Progress, Jonathan Stover, Siegwart Mayr

Campus Research Day

Digital natives are constantly surrounded by technology. Therefore, traditional methods of teaching are becoming obsolete and increasingly creative solutions are required to keep students engaged. Among these solutions is a concept called game based learning. Game based learning is a unique educational experience that incorporates the engagement factors of video games with education. Even though it is still in an early stage of adoption, game based learning has been proven to be a surprisingly effective tool for providing students with a valuable educational experience. Even with this evidence in mind, current game based learning programs still hold the potential to …

A Comprehensive Study On Crypto-Algorithms, Sucheta Panda, Sushree Bibhuprada B. Priyadarshini

International Journal of Smart Sensor and Adhoc Network

In the field of computer network and security, cryptography plays a vital role for secure data transmission as it follows the principle of data confidentiality, integrity, non-repudiation, authentication. By using several cryptographic algorithms, a user can deliver and receive the message in more convenient way. In this paper, we have collaborated on various cryptographic algorithms, several types of cryptographic techniques along with different types of security attacks prevailing in case of cryptography. During the exchanging of any sort of information, the key generation, encryption and decryption processes are examined in more details in the current paper. We have discussed regarding …

Open Resources For Teaching Iot Physical Security, Maria Valero

All Things Open

The Internet of Things (IoT) and physical devices are around us all the time. From a simple watch that measures your heartbeat to an advanced voice assistant that turns on your light, IoT devices are everywhere. Teaching security in this type of physical device is a new topic, and finding good quality resources for teaching is also a complicated task. In this project, the instructor took the best online open-source materials and created 15 modules with hands-on activities that teach students about the interaction with IoT devices and their security. The materials include labs with emulators of physical devices like …

Assessing The Ability Of Arduino-Based Sensor Systems To Monitor Changes In Water Quality, Josiah Hacker

Honors College Theses

Access to safe water is vital to public health. While developed countries like the United States are recognized as having reliable and safe water, many small water utilities struggle with supplying consistent water quality. Technicians of these utilities will periodically test water samples from the influent and throughout the distribution system. However, this laborious and costly process does not capture sudden changes in influent water quality due to environmental conditions or pipes breaking in the distribution system. Here I show how an Arduino-based sensor can be used as a real-time, low-cost monitor of water quality parameters. Specifically, I developed a …

The Fashion Visual Search Using Deep Learning Approach, Smita V. Bhoir, Sunita R. Patil

Library Philosophy and Practice (e-journal)

In recent years, the World Wide Web (WWW) has established itself as a popular source of information. Using an effective approach to investigate the vast amount of information available on the internet is essential if we are to make the most of the resources available. Visual data cannot be indexed using text-based indexing algorithms because it is significantly larger and more complex than text. Content-Based Image Retrieval, as a result, has gained widespread attention among the scientific community (CBIR). Input into a CBIR system that is dependent on visible features of the user's input image at a low level is …

Investigating The Use Of Recurrent Neural Networks In Modeling Guitar Distortion Effects, Caleb Koch, Scott Hawley, Andrew Fyfe

Belmont University Research Symposium (BURS)

Guitar players have been modifying their guitar tone with audio effects ever since the mid-20th century. Traditionally, these effects have been achieved by passing a guitar signal through a series of electronic circuits which modify the signal to produce the desired audio effect. With advances in computer technology, audio “plugins” have been created to produce audio effects digitally through programming algorithms. More recently, machine learning researchers have been exploring the use of neural networks to replicate and produce audio effects initially created by analog and digital effects units. Recurrent Neural Networks have proven to be exceptional at modeling audio effects …

Accurate Indoor Navigation System Based On Imu/Lp-Mm Integrated Method Using Kalman Filter Algorithm, Abdullah Mohammed Bahasan

Hadhramout University Journal of Natural & Applied Sciences

Abstract

The demand for navigation systems is rapidly increasing, especially in indoor environments which the signal of GPS is not available. Therefore the Inertial Measurement Unit (IMU) system is a suitable navigation system in such indoor environments. It usually consists of three accelerometers and three gyroscopes to determine position, velocity and attitude information, respectively, without need of any external source. But this type of navigation systems has errors growth with time due to accelerometers and gyroscopes drifts. This paper introduces indoor navigation system based on integrated IMU navigation system with proposed system called Landmarks Points-Map Matching (LP-MM) system using Kalman …

Self-Learning Algorithms For Intrusion Detection And Prevention Systems (Idps), Juan E. Nunez, Roger W. Tchegui Donfack, Rohit Rohit, Hayley Horn

SMU Data Science Review

Today, there is an increased risk to data privacy and information security due to cyberattacks that compromise data reliability and accessibility. New machine learning models are needed to detect and prevent these cyberattacks. One application of these models is cybersecurity threat detection and prevention systems that can create a baseline of a network's traffic patterns to detect anomalies without needing pre-labeled data; thus, enabling the identification of abnormal network events as threats. This research explored algorithms that can help automate anomaly detection on an enterprise network using Canadian Institute for Cybersecurity data. This study demonstrates that Neural Networks with Bayesian …

Evolution And Enlightenment Of Us-Japan “Advanced Storage Research Consortium”, Sumei Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

In the process of comprehensively promoting Chinese-style modernization, we must adhere to scientific and technological selfreliance and self-improvement as the strategic support for national development, and scientific and technological innovation is the main driving force for high-quality economic development. As one of the carriers, the innovation consortium formed by enterprises as main entities aims to realize the deep integration of innovation chain and industrial chain, accelerating the transformation of scientific and technological achievements into real productivity, and solving the problem of disconnection between scientific research activities and industrial demand. On the basis of reviewing and summarizing the evolution of the …

Ai Applications On Planetary Rovers, Alexis David Pascual

Electronic Thesis and Dissertation Repository

The rise in the number of robotic missions to space is paving the way for the use of artificial intelligence and machine learning in the autonomy and augmentation of rover operations. For one, more rovers mean more images, and more images mean more data bandwidth required for downlinking as well as more mental bandwidth for analyzing the images. On the other hand, light-weight, low-powered microrover platforms are being developed to accommodate the drive for planetary exploration. As a result of the mass and power constraints, these microrover platforms will not carry typical navigational instruments like a stereocamera or a laser …

The Rise And Risks Of Internet Of Things, Diamond E. Hicks

Cybersecurity Undergraduate Research

Internet of Things (IoT) has become a necessary part of our everyday lives. IoT is the network in which many different devices communicate, connect, and share data. Though how IoT got to where it is today, the issues it faced, and how it affects our lives today is not common knowledge. Despite the fact that IoT has advanced our technology to what it is today, people do not completely understand what it does.

Multi-Class Brain Tumor Detection Using Convolutional Neural Network, Mukul Dhurkunde Graduate Engineer, Nayan Kadam Graduate Engineer, Mohak Trivedi Graduate Engineer, Sandeep Maru Graduate Engineer, Prajakta Shirke Assistant Professor

Graduate Research in Engineering and Technology (GRET)

Brain tumour detection is one of the most critical and arduous function in the domain of healthcare. Brain tumour, if not detected at an early stage, can be fatal. At the present time, detection and classification of brain tumour is done by the method of Biopsy which is very time-consuming and complex. . By looking at the brain MRI or CT scan, it is possible for the experts to identify whether tumour is present or not and the region of the tumour, but it is difficult to identify the small dissimilarities in the structure of tumour and classify it into …

Phone Microwave, Khanh Kim Hoang, Emily Zhou

Computer Engineering

This project involves the installation of remote-control capabilities in an antique 1980s microwave, effectively turning the microwave into a “smart” device. While preserving the original functionality of the microwave, a combination of software and hardware components allows for remote microwave operations. The microwave can be remotely operated by calling the built-in number, and more advanced settings and options can be utilized by texting. The microwave is also secured against unauthorized use with the addition of a PIN code that is required to operate the device.

Procedural Model Of The Monitoring System, Fayzullajon Botirov

Chemical Technology, Control and Management

This article discusses the process of monitoring information security incidents and factors affecting the effectiveness of monitoring. A procedural model of the functioning of the information security incident monitoring system is constructed, based on the study of its structure, the principles of operation of individual components and literature data, the analysis of individual stages.

Comprehensive Wind Speed Forecasting-Based Analysis Of Stacked Stateful & Stateless Models, Swayamjit Saha, Amogu Uduka, Hunter Walt, James Lucore

Graduate Research Symposium

Wind speed is a powerful source of renewable energy, which can be used as an alternative to the non-renewable resources for production of electricity. Renewable sources are clean, infinite and do not impact the environment negatively during production of electrical energy. However, while eliciting electrical energy from renewable resources viz. solar irradiance, wind speed, hydro should require special planning failing which may result in huge loss of labour and money for setting up the system. In this poster, we discuss four deep recurrent neural networks viz. Stacked Stateless LSTM, Stacked Stateless GRU, Stacked Stateful LSTM and Statcked Stateful GRU which …

Cognitive Software Defined Networking And Network Function Virtualization And Applications, Sachin Sharma, Avishek Nag

Articles

The emergence of Software-Defined Networking (SDN) and Network Function Virtualization (NFV) has revolutionized the Internet. Using SDN, network devices can be controlled from a centralized, programmable control plane that is decoupled from their data plane, whereas with NFV, network functions (such as network address translation, firewall, and intrusion detection) can be virtualized instead of being implemented on proprietary hardware. In addition, Artificial Intelligence (AI) and Machine Learning (ML) techniques will be key to automating network operations and enhancing customer service. Many of the challenges behind SDN and NFV are currently being investigated in several projects all over the world using …

Proposed Mitigation Framework For The Internet Of Insecure Things, Mahmoud M. Elgindy, Sally M. Elghamrawy, Ali I. El-Desouky

Mansoura Engineering Journal

Intrusion detection systems IDS are increasingly utilizing machine learning methods. IDSs are important tools for ensuring the security of network data and resources. The Internet of Things (IoT) is an expanding network of intelligent machines and sensors. However, they are vulnerable to attackers because of the ubiquitous and extensive IoT networks. Datasets from intrusion detection systems (IDS) have been analyzed deep learning methods such as Bidirectional long-short term memory (BiLSTM). This research presents an BiLSTM intrusion detection framework with Principal Component Analysis PCA (PCA-LSTM-IDS). The PCA-LSTM-IDS is comprised of two layers: extracting layer which using PCA, and the anomaly BiLSTM …

Resource Management In Mobile Edge Computing For Compute-Intensive Application, Xiaojie Zhang

Dissertations, Theses, and Capstone Projects

With current and future mobile applications (e.g., healthcare, connected vehicles, and smart grids) becoming increasingly compute-intensive for many mission-critical use cases, the energy and computing capacities of embedded mobile devices are proving to be insufficient to handle all in-device computation. To address the energy and computing shortages of mobile devices, mobile edge computing (MEC) has emerged as a major distributed computing paradigm. Compared to traditional cloud-based computing, MEC integrates network control, distributed computing, and storage to customizable, fast, reliable, and secure edge services that are closer to the user and data sites. However, the diversity of applications and a variety …