Systems and Communications Commons^™

Social Distancing Monitoring System Using Deep Learning, Amelia Ritahani Ismail, Nur Shairah Muhd Affendy, Asmarani Ahmad Puzi

Knowledge Engineering and Data Science

COVID-19 has been declared a pandemic in the world by 2020. One way to prevent COVID-19 disease, as the World Health Organization (WHO) suggests, is to keep a distance from other people. It is advised to stay at least 1 meter away from others, even if they do not appear to be sick. The reason is that people can also be the virus carrier without having any symptoms. Thus, many countries have enforced the rules of social distancing in their Standard Operating Procedure (SOP) to prevent the virus spread. Monitoring the social distance is challenging as this requires authorities to …

Automatic 3d Cranial Landmark Positioning Based Onsurface Curvature Feature Using Machine Learning, Putu Hendra Suputra, Anggraini Dwi Sensusiati, Myrtati Dyah Artaria, Gijsbertus Jacob Verkerke, Eko Mulyanto Yuniarno, I Ketut Eddy Purnama

Knowledge Engineering and Data Science

Cranial anthropometric reference points (landmarks) play an important role in craniofacial reconstruction and identification. Knowledge to detect the position of landmarks is critical. This work aims to locate landmarks automatically. Landmarks positioning using Surface Curvature Feature (SCF) is inspired by conventional methods of finding landmarks based on morphometrical features. Each cranial landmark has a unique shape. With the appropriate 3D descriptors, the computer can draw associations between shapes and landmarks using machine learning. The challenge in classification and detection in three-dimensional space is to determine the model and data representation. Using three-dimensional raw data in machine learning is a serious …

The Effect Of Resampling On Classifier Performance: Anempirical Study, Utomo Pujianto, Muhammad Iqbal Akbar, Niendhitta Tamia Lassela, Deni Sutaji

Knowledge Engineering and Data Science

An imbalanced class on a dataset is a common classification problem. The effect of using imbalanced class datasets can cause a decrease in the performance of the classifier. Resampling is one of the solutions to this problem. This study used 100 datasets from 3 websites: UCI Machine Learning, Kaggle, and OpenML. Each dataset will go through 3 processing stages: the resampling process, the classification process, and the significance testing process between performance evaluation values of the combination of classifier and the resampling using paired t-test. The resampling used in the process is Random Undersampling, Random Oversampling, and SMOTE. The classifier …

A Comparison Of Machine Learning Models To Prioritise Emailsusing Emotion Analysis For Customer Service Excellence, Mohammad Yasser Chuttur, Yashinee Parianen

Knowledge Engineering and Data Science

There has been little research on machine learning for email prioritization for customer service excellence. To fill this gap, we propose and assess the efficacy of various machine learning techniques for classifying emails into three degrees of priority: high, low, and neutral, based on the emotions inherent in the email content. It is predicted that after emails are classified into those three categories, recipients will be able to respond to emails more efficiently and provide better customer service. We use the NRC Emotion Lexicon to construct a labeled email dataset of 517,401 messages for our proposal. Following that, we train …

Fish Image Classification Using Transfer Learning Method Withadaptive Learning Rate, Rizka Suhana, Wayan Firdaus Mahmudy, Agung Setia Budi

Knowledge Engineering and Data Science

The diversity of fish species in coral reef ecosystems is one of the indications in determining health in coral reef ecosystems. Many Indonesian Fisheries and Marine Research and Development Agency experts carefully classify fish images. A reliable technique for performing image classification is Convolutional Neural Network (CNN). Transfer learning appears and adopts part of CNN, namely the modified convolution layer. The paper aims to solve the fish classification problem using the pre-trained model of Mobilenet V2. The model has a low computational process and does not use too many memory resources when training image data. The research image data used …

Human Facial Expressions Identification Using Convolutionalneural Network With Vgg16 Architecture, Luther Alexander Latumakulita, Sandy Laurentius Lumintang, Deiby Tineke Salaki, Steven R. Sentinuwo, Alwin Melkie Sambul, Noorul Islam

Knowledge Engineering and Data Science

The human facial expression identification system is essential in developing human interaction and technology. The development of Artificial Intelligence for monitoring human emotions can be helpful in the workplace. Commonly, there are six basic human expressions, namely anger, disgust, fear, happiness, sadness, and surprise, that the system can identify. This study aims to create a facial expression identification system based on basic human expressions using the Convolutional Neural Network (CNN) with a 16-layer VGG architecture. Two thousand one hundred thirty-seven facial expression images were selected from the FER2013, JAFFE, and MUG datasets. By implementing image augmentation and setting up the …

Sentiment Analysis Of Amazon Product Reviews Usingsupervised Machine Learning Techniques, Naveed Sultan

Knowledge Engineering and Data Science

Today, everything is sold online, and many individuals can post reviews about different products to show feedback. Serves as feedback for businesses regarding buyer reviews, performance, product quality, and seller service. The project focuses on buyer opinions based on Mobile Phone reviews. Sentiment analysis is the function of analyzing all these data, obtaining opinions about these products and services that classify them as positive, negative, or neutral. This insight can help companies improve their products and help potential buyers make the right decisions. Once the preprocessing is classified on a trained dataset, these reviews must be preprocessed to remove unwanted …

Empirical Models Of 3d Air-To-Air Communication Channels, Neil Matson

Electrical Engineering Theses and Dissertations

Unmanned Aerial Vehicles (UAVs) often lack the size, weight, and power to support large antenna arrays or a large number of radio chains. Despite such limitations, emerging applications that require the use of swarms, where UAVs form a pattern and coordinate towards a common goal, must have the capability to transmit in any direction in three-dimensional (3D) space from moment to moment. In this work, we design a measurement study to evaluate the role of antenna polarization diversity on UAV systems communicating in arbitrary 3D space. To do so, we construct flight patterns where one transmitting UAV is hovering at …

Real-Time Data Analytics For Monitoring Electricity Consumption Using Iot Technology, Waheed Muhammad Sanya, Gaurav Bajpai, Omar Haji Kombo, Evariste Twahirwa

Tanzania Journal of Engineering and Technology (TJET)

Rising electricity bills as a result of climate variability and new home electrical and electronic appliances are becoming a major source of concern for most end users. Consumers are typically unaware of their household electricity consumption patterns and the costs associated with them, making proper planning and budgeting difficult. Monitoring and controlling energy consumption on appliances can reduce energy costs for end-users. The Internet of Things (IoT) has the potential to provide remote monitoring and control of devices via automated monitoring and control. In this study, we propose an IoT-enabled system for monitoring and controlling energy consumption in homes to …

Group-Based Data Offloading Techniques Assisted By D2d Communication In 5g Mobile Network, Juma S Ally

Tanzania Journal of Engineering and Technology (TJET)

Machine type communication devices proposed as one of the substantial data collections in the 5G of wireless networks. However, the existing mobile communication network is not designed to handle massive access from the MTC devices instead of human type communication. In this context, we propose the device-to-device communication assisted a mobile terminal (smartphone) on data computing, focusing on data generated from a correlated source of machine type communication devices. We consider the scenario that the MTC devices after collecting the data will transmit to a smartphone for computing. With the limitation of computing resources at the smartphone, some data are …

Digital Skills And Self-Employment Among Graduates Of Technical Higher Education Institutions In Tanzania, Charles Raphael

Tanzania Journal of Engineering and Technology (TJET)

Digital skills are the driving forces for innovative, inclusive and sustainable growth through innovations and digitalization which in turn stimulate job creation, alleviate poverty, reducing inequality, facilitating the delivery of goods and services. However, large number of graduates is shown to be weak in digital skills in the industry hence affect their employability including self-employment. Recently, the Technical Higher Education Institutions (THEIs) took some initiatives to instill the digital skills to their respective students. This study therefore assessed the level of competence of digital skills among graduates following the initiatives taken by the THEIs and their influence on self-employment. It …

Implementation Of Digital Transformation In The Technical Higher Education Institutions In Tanzania, Charles Raphael

Tanzania Journal of Engineering and Technology (TJET)

Digital transformation has been prioritized recently in this era of fourth industrial revolution by various organizations for maintaining strong competitive advantage, especially in the fourth industrial revolution. The higher education institutions must likewise adopt and implement digital transformation to enrich their students with the knowledge, experience and the skills they need for a very different future. Technical higher education institutions are inevitable in the given transformation. However, very little is known regarding adoption of digital transformation in the given institutions. This study therefore examined the level of adoption of digital services in the technical higher education institutions in Tanzania. It …

Efficient And Simple Heuristic Algorithm For Portfolio Optimization Collether John, Collether John

Tanzania Journal of Engineering and Technology (TJET)

Markowitz model considers what is termed as standard portfolio optimization. The portfolio optimization problem is a problem which based on asset allocation and diversification for maximum return with minimum risk. Thus, the standard portfolio optimization problem happens when the constraints considered are budget and no-short selling. In reality however, portfolio optimization has realistic constraints to be incorporated such as holding sizes, cardinality and transaction cost. When realistic constraints are added into portfolio optimization problem, it becomes too complex to be solved by standard optimization methods which in this case turns to be an extended portfolio optimization problem. Markowitz solution and …

Analyzing The Influence Of Smart-Device Visual Features, Viewing Distance And Content Factors On Video Streaming Qoe, Alex Frank Mongi

Tanzania Journal of Engineering and Technology (TJET)

Quality of experience (QoE) over wireless networks has attracted attention from industry and academia due to an increase in video streaming applications. Several researchers have attempted to understand the factors affecting QoE and design appropriate quality control strategies. Normally, video streaming is initiated by a user who accesses video content over a network using a smart device that may be held at various viewing distances. Each aforementioned factor has the potential to affect QoE. However, several studies explore the behavior of wireless networks on video streaming QoE. To understand the effects of other factors on QoE, this paper investigates the …

Cyber Security Challenges, Its Emerging Trends On Latest Information And Communication Technology And Cyber Crime In Mobile Money Transaction Services, Hakeem J. Pallangyo

Tanzania Journal of Engineering and Technology (TJET)

This paper investigates the challenges emerging trends on latest Information and Communication Technology and cybercrime in mobile money transaction services in Tanzania. The objective of this is to evaluate the challenges associated with this rapid growth in ICT and to determine factors influencing Cybersecurity readiness and Cybercrimes in mobile money transaction services. Cyber Security plays a significant role in the field of Information and Communication Technology especially on mobile money transaction services. The study recognizes the provision of mobile money services by both telecommunication companies and local banks, the fact is that whenever we think about the cyber security, the …

Soft-Mask De-Mixing For Anechoic Mixtures, Swarnadeep Bagchi, Ruairí De Fréin

Articles

This paper extends a computationally efficient, soft-mask based source separation (SS) technique called Redress, to anechoic mixing scenarios. SS methods are an integral part of hearing aid research. We call the resulting method D-Redress. In its original form, Redress was intended for instantaneous mixing scenarios. Numerical evaluations demonstrate that soft-mask based techniques reduce the level of artifacts in the separated speech. Monte Carlo trials on 1000 real speech mixtures demonstrate that the D-Redress successfully extends Redress in terms of Overall-Perceptual (OPS), Target-Perceptual (TPS) scores and Human-Ear Intelligibility (HEI).

Barrier Knockdown Test Control System For The Cal Poly Kinesiology Department, Regina M. Chapuis

Computer Engineering

The goal of this project is to design and implement a new control system for the LEDs and buttons on an existing Barrier Knockdown setup in the Cal Poly Kinesiology department. The Barrier Knockdown test is a testing apparatus in which subjects knock down a series of mechanical barriers in one of three patterns. The computer system times their reaction and movement time, and the test as a whole provides students with data to study the phenomenon of Contextual Interference. This system was previously controlled by an old computer setup that ultimately crashed. This project recreates the logic and user …

Imnets: Deep Learning Using An Incremental Modular Network Synthesis Approach For Medical Imaging Applications, Redha A. Ali, Russell C. Hardie, Barath Narayanan Narayanan, Temesguen Messay

Electrical and Computer Engineering Faculty Publications

Deep learning approaches play a crucial role in computer-aided diagnosis systems to support clinical decision-making. However, developing such automated solutions is challenging due to the limited availability of annotated medical data. In this study, we proposed a novel and computationally efficient deep learning approach to leverage small data for learning generalizable and domain invariant representations in different medical imaging applications such as malaria, diabetic retinopathy, and tuberculosis. We refer to our approach as Incremental Modular Network Synthesis (IMNS), and the resulting CNNs as Incremental Modular Networks (IMNets). Our IMNS approach is to use small network modules that we call SubNets …

Hvac Hardware Modeling Using Programmable Automatic Controller, Panthil Ketan Patel, Lumanti Tuladhar

Electrical Engineering

The primary purpose of this project is to use the donated programmable logic controllers (PLC) from Schneider Electric to develop experiments for a future lab class at Cal Poly. Our goal as the first group working on this project is to develop an experiment where the PLC can control the HVAC system based on temperature and humidity sensors and user inputs to maintain a desired consistent temperature. The PLC will be controlled using Unity Pro XLS/Control Expert software for simulations. The overall purpose of the experiments will be to demonstrate the potential of the PLC to minimize manual intervention while …

Mars Prototype Rover Environmental Measurement System, James A. Renick

Computer Engineering

In my senior project, the problem I am trying to solve is how to efficiently design, create, and install an original library onto a Mars prototype rover operating system and to further use that library to integrate a new weather measurement sensor device into the rover system with the necessary software and hardware implementations. This is an important and highly valued problem as many aerospace and other engineering companies utilize rovers and other autonomous systems for important research, explorations, and reconnaissance missions and goals. In solving this problem, I utilized many resources that were available to me such as advisors, …

Developing A Miniature Smart Boat For Marine Research, Michael Isaac Eirinberg

Computer Engineering

This project examines the development of a smart boat which could serve as a possible marine research apparatus. The smart boat consists of a miniature vessel containing a low-cost microcontroller to live stream a camera feed, GPS telemetry, and compass data through its own WiFi access point. The smart boat also has the potential for autonomous navigation. My project captivated the interest of several members of California Polytechnic State University, San Luis Obispo’s (Cal Poly SLO) Marine Science Department faculty, who proposed a variety of fascinating and valuable smart boat applications.

Smart Bottle Ble Integration, Joshua M. Rizzolo

Electrical Engineering

In 1975, four percent of children aged five to nineteen were categorized as overweight or obese. As of 2016, this figure climbed above 18 percent [1]. Researchers at California Polytechnic State University San Luis Obispo (Cal Poly) want to investigate the effect of overeating in early childhood on later childhood obesity. This research requires collecting feeding pattern data on infants, which proves challenging. Parents cannot be relied on to regularly collect clean data due to factors including work schedule, multitasking, and general exhaustion. Thus, we have developed a tool to automatically collect data on feeding frequency and duration, as well …

X-Band Rf Transmitter Design For Multi-Purpose Small Satellite Communication Operations, Omer F. Gumus

Master's Theses

This thesis provides a description of the analysis, design, and tests of an X-band RF Transmitter communication system for small satellites. X-band transmitter systems are becoming popular in the upcoming deep space missions. Most of the deep-space ground stations have been using X-band frequencies to receive or transmit signals. The X-band (<10 GHz) can offer lower atmospheric losses and up to a couple of Mbps data rates for multiple satellite operations. Nowadays, many small satellites have been using frequency bands such as VHF, UHF, L, and S-band frequencies for communication. From deep space to the ground station, the low-frequency ranges are inadequate in providing Mbps level data rates and enough bandwidth for deep space missions.

The main focus of this thesis was the development of the subsystems such as gain block amplifier, Mixer, Bandpass Filter, and RF power amplifier. The subsystems were designed separately, then they were connected together to perform an end-to-end system test. One of the thesis aims is to design …

Private Information Retrieval And Function Computation For Noncolluding Coded Databases, Sarah A. Obead

Dissertations

The rapid development of information and communication technologies has motivated many data-centric paradigms such as big data and cloud computing. The resulting paradigmatic shift to cloud/network-centric applications and the accessibility of information over public networking platforms has brought information privacy to the focal point of current research challenges. Motivated by the emerging privacy concerns, the problem of private information retrieval (PIR), a standard problem of information privacy that originated in theoretical computer science, has recently attracted much attention in the information theory and coding communities. The goal of PIR is to allow a user to download a message from a …

Graph-Based Heuristic Solution For Placing Distributed Video Processing Applications On Moving Vehicle Clusters, Kanika Sharma, Bernard Butler, Brendan Jennings

Articles

Vehicular fog computing (VFC) is envisioned as an extension of cloud and mobile edge computing to utilize the rich sensing and processing resources available in vehicles. We focus on slow-moving cars that spend a significant time in urban traffic congestion as a potential pool of onboard sensors, video cameras, and processing capacity. For leveraging the dynamic network and processing resources, we utilize a stochastic mobility model to select nodes with similar mobility patterns. We then design two distributed applications that are scaled in real-time and placed as multiple instances on selected vehicular fog nodes. We handle the unstable vehicular environment …

Ml-Based Online Traffic Classification For Sdns, Mohammed Nsaif, Gergely Kovasznai, Mohammed Abboosh, Ali Malik, Ruairí De Fréin

Articles

Traffic classification is a crucial aspect for Software-Defined Networking functionalities. This paper is a part of an on-going project aiming at optimizing power consumption in the environment of software-defined datacenter networks. We have developed a novel routing strategy that can blindly balance between the power consumption and the quality of service for the incoming traffic flows. In this paper, we demonstrate how to classify the network traffic flows so that the quality of service of each flow-class can be guaranteed efficiently. This is achieved by creating a dataset that encompasses different types of network traffic such as video, VoIP, game …

A Harmonic Radar System For Honey Bee Tracking To Better Understand Colony Collapse Disorder, William B. Woo

Theses and Dissertations

Honey bees are some of the most important pollinators for agriculture in the world and are pivotal to the health of worldwide ecosystems. Like all insects, bees struggle with exposure to parasites, diseases, and other environmental factors that can negatively affect the overall health of the colony. Recently, a new unexplainable phenomenon called Colony Collapse Disorder (CCD) has been wreaking havoc on bee populations worldwide. As a result, a system capable of tracking bees is required to understand the different contributions of chemicals, parasites, etc. to CCD. This research seeks to show data supporting the development of systems for an …

Structural Checking Tool Restructure And Matching Improvements, Derek Taylor

Graduate Theses and Dissertations

With the rising complexity and size of hardware designs, saving development time and cost by employing third-party intellectual property (IP) into various first-party designs has become a necessity. However, using third-party IPs introduces the risk of adding malicious behavior to the design, including hardware Trojans. Different from software Trojan detection, the detection of hardware Trojans in an efficient and cost-effective manner is an ongoing area of study and has significant complexities depending on the development stage where Trojan detection is leveraged. Therefore, this thesis research proposes improvements to various components of the soft IP analysis methodology utilized by the Structural …

State Estimation—Beyond Gaussian Filtering, Haozhan Meng

LSU New Orleans Theses and Dissertations

This dissertation considers the state estimation problems with symmetric Gaussian/asymmetric skew-Gaussian assumption under linear/nonlinear systems. It consists of three parts. The first part proposes a new recursive finite-dimensional exact density filter based on the linear skew-Gaussian system. The second part adopts a skew-symmetric representation (SSR) of distribution for nonlinear skew-Gaussian estimation. The third part gives an optimized Gauss-Hermite quadrature (GHQ) rule for numerical integration with respect to Gaussian integrals and applies it to nonlinear Gaussian filters.

We first develop a linear system model driven by skew-Gaussian processes and present the exact filter for the posterior density with fixed dimensional recursive …

A Novel Data Lineage Model For Critical Infrastructure And A Solution To A Special Case Of The Temporal Graph Reachability Problem, Ian Moncur

Graduate Theses and Dissertations

Rapid and accurate damage assessment is crucial to minimize downtime in critical infrastructure. Dependency on modern technology requires fast and consistent techniques to prevent damage from spreading while also minimizing the impact of damage on system users. One technique to assist in assessment is data lineage, which involves tracing a history of dependencies for data items. The goal of this thesis is to present one novel model and an algorithm that uses data lineage with the goal of being fast and accurate. In function this model operates as a directed graph, with the vertices being data items and edges representing …