Engineering Commons^™

Simple Modification For An Apriori Algorithm With Combination Reduction And Iteration Limitation Technique, Adie Wahyudi Oktavia Gama, Ni Made Widnyani

Knowledge Engineering and Data Science

Apriori algorithm is one of the methods with regard to association rules in data mining. This algorithm uses knowledge from an itemset previously formed with frequent occurrence frequencies to form the next itemset. An a priori algorithm generates a combination by iteration methods that are using repeated database scanning process, pairing one product with another product and then recording the number of occurrences of the combination with the minimum limit of support and confidence values. The a priori algorithm will slow down to an expanding database in the process of finding frequent itemset to form association rules. Modification techniques are …

Segmentation Method For Face Modelling In Thermal Images, Albar Albar, Hendrick Hendrick, Rahmat Hidayat

Knowledge Engineering and Data Science

Face detection is mostly applied in RGB images. The object detection usually applied the Deep Learning method for model creation. One method face spoofing is by using a thermal camera. The famous object detection methods are Yolo, Fast Region Based Convolutional Neural Networks (RCNN), Faster RCNN, SSD, and Mask RCNN. We proposed a segmentation Mask RCNN method to create a face model from thermal images. This model was able to locate the face area in images. The dataset was established using 1600 images. The images were created from direct capturing and collecting from the online dataset. The Mask RCNN was …

Generating Javanese Stopwords List Using K-Means Clustering Algorithm, Aji Prasetya Wibawa, Hidayah Kariima Fithri, Ilham Ari Elbaith Zaeni, Andrew Nafalski

Knowledge Engineering and Data Science

Stopword removal necessary in Information Retrieval. It can remove frequently appeared and general words to reduce memory storage. The algorithm eliminates each word that is precisely the same as the word in the stopword list. However, generating the list could be time-consuming. The words in a specific language and domain must be collected and validated by specialists. This research aims to develop a new way to generate a stop word list using the K-means Clustering method. The proposed approach groups words based on their frequency. The confusion matrix calculates the difference between the findings with a valid stopword list created …

Authentication Based On Blockchain, Norah Alilwit

Doctoral Dissertations and Master's Theses

Across past decade online services have enabled individuals and organizations to perform different types of transactions such as banking, government transactions etc. The online services have also enabled more developments of applications, at cheap cost with elastic and scalable, fault tolerant system. These online services are offered by services providers which are use authentication, authorization and accounting framework based on client-server model. Though this model has been used over decades, study shows it is vulnerable to different hacks and it is also inconvenient to use for the end users. In addition, the services provider has total control over user data …

Efficient Scheduling Of Plantation Company Workers Using Genetic Algorithm, Wayan Firdaus Mahmudy, Andreas Pardede, Agus Wahyu Widodo, Muh Arif Rahman

Knowledge Engineering and Data Science

Workers at large plantation companies have various activities. These activities include caring for plants, regularly applying fertilizers according to schedule, and crop harvesting activities. The density of worker activities must be balanced with efficient and fair work scheduling. A good schedule will minimize worker dissatisfaction while also maintaining their physical health. This study aims to optimize workers' schedules using a genetic algorithm. An efficient chromosome representation is designed to produce a good schedule in a reasonable amount of time. The mutation method is used in combination with reciprocal mutation and exchange mutation, while the type of crossover used is one …

A Review Of Accessing Big Data With Significant Ontologies, Jumah Y.J Sleeman, Jehad A.H Hammad

Knowledge Engineering and Data Science

Ontology Based Data Access (OBDA) is a recently proposed approach which is able to provide a conceptual view on relational data sources. It addresses the problem of the direct access to big data through providing end-users with an ontology that goes between users and sources in which the ontology is connected to the data via mappings. We introduced the languages used to represent the ontologies and the mapping assertions technique that derived the query answering from sources. Query answering is divided into two steps: (i) Ontology rewriting, in which the query is rewritten with respect to the ontology into new …

Convolutional Neural Network On Tanned And Synthetic Leather Textures, Faadihilah Ahnaf Faiz, Ahmad Azhari

Knowledge Engineering and Data Science

Tanned leather is an output from complex processes called tanning. Leather tanning is an important step that used to protect the fiber or protein structure of animal’s skin. Another reason of tanning process is to prevent the animal’s skin from any defect or rot. After the tanning is complete, the leather can be applied to produce a wide variety of leather products. Thus, the leather prices usually more expensive because it takes longer time in process. Another way to get cheaper price is make non-animal leather that usually known as synthetic or imitation leather. The purpose of this paper is …

A Circle Hough Transform Implementation Using High-Level Synthesis, Carlos Lemus

UNLV Theses, Dissertations, Professional Papers, and Capstones

Circle Hough Transform (CHT) has found applications in biometrics, robotics, and imageanalysis. In this work, the focus is the development of a Field Programmable Gate Array (FPGA) based accelerator that performs a series of procedures and results in circle detection. The design is performed using Vivado High-Level Synthesis (HLS) tools and targeted for a Zynq UltraScale+ ZCU106. The implementation includes the following procedures: Gaussian filter, Sobel edge operator, thresholding, and finally the CHT algorithm. The performance is evaluated based on the execution time as compared to the software (Python code) execution and the analysis tools provided by Vivado HLS tool. …

A Multi-Channel Mcp-Pmt Based Readout Integrated Circuit For Lidar Applications, Sachin Purushothaman Namboodiri

UNLV Theses, Dissertations, Professional Papers, and Capstones

Photon counting techniques are becoming more critical in fields such as LiDAR, high energy physics (HEP), and positron emission tomography (PET). For space-based aerosol-cloud-ocean (ACO) LiDAR, the total aggregate photon flux signal has a very high dynamic range, from a single-photon up to giga-photons per second for a single channel. This dissertation focuses on the design of a multichannel, photon counting readout circuit that can interface with MCP-PMTs for high dynamic range, space-based LiDAR applications. Chapter 2 presents the conventional current mode approach that has been employed to realize a photon counting circuit. A transimpedance amplifier, a 6-bit delay line …

Towards Sensorimotor Coupling Of A Spiking Neural Network And Deep Reinforcement Learning For Robotics Application, Kashu Yamazaki

Mechanical Engineering Undergraduate Honors Theses

Deep reinforcement learning augments the reinforcement learning framework and utilizes the powerful representation of deep neural networks. Recent works have demonstrated the great achievements of deep reinforcement learning in various domains including finance,medicine, healthcare, video games, robotics and computer vision.Deep neural network was started with multi-layer perceptron (1stgeneration) and developed to deep neural networks (2ndgeneration)and it is moving forward to spiking neural networks which are knownas3rdgeneration of neural networks. Spiking neural networks aim to bridge the gap between neuroscience and machine learning, using biologically-realistic models of neurons to carry out computation. In this thesis, we first provide a comprehensive review …

Identifying Depressive Symptoms From Tweets: Figurative Language Enabled Multitask Learning Framework, Shweta Yadav, Jainish Chauhan, Joy Prakash Sain, Krishnaprasad Thirunarayan, Amit P. Sheth, Jeremiah Schumm

Publications

Existing studies on using social media for deriving mental health status of users focus on the depression detection task. However, for case management and referral to psychiatrists, healthcare workers require practical and scalable depressive disorder screening and triage system. This study aims to design and evaluate a decision support system (DSS) to reliably determine the depressive triage level by capturing fine-grained depressive symptoms expressed in user tweets through the emulation of Patient Health Questionnaire-9 (PHQ-9) that is routinely used in clinical practice. The reliable detection of depressive symptoms from tweets is challenging because the 280-character limit on tweets incentivizes the …

Global Privacy Concerns Of Facial Recognition Big Data, Myranda Westbrook

Honors Theses

Facial recognition technology is a system of automatic acknowledgement that recognizes individuals by categorizing specific features of their facial structure to link the scanned information to stored data. Within the past few decades facial recognition technology has been implemented on a large scale to increase the security measures needed to access personal information. This has been specifically used in surveillance systems, social media platforms, and mobile device access control. The extensive use of facial recognition systems has created challenges as it relates to biometric information control and privacy concerns. This concern raises the cost and benefit analysis of an individual’s …

Automatic Target Recognition With Convolutional Neural Networks., Nada Baili

Electronic Theses and Dissertations

Automatic Target Recognition (ATR) characterizes the ability for an algorithm or device to identify targets or other objects based on data obtained from sensors, being commonly thermal. ATR is an important technology for both civilian and military computer vision applications. However, the current level of performance that is available is largely deficient compared to the requirements. This is mainly due to the difficulty of acquiring targets in realistic environments, and also to limitations of the distribution of classified data to the academic community for research purposes. This thesis proposes to solve the ATR task using Convolutional Neural Networks (CNN). We …

Cloud Computing Service Interoperability And Architectural Concepts, Anmar Salih

Theses and Dissertations

Today’s market with a vast number of Cloud-computing providers creates a challenge for practical cooperation between the various provider cloud service platforms. Not only does Cloud interoperability provide this needed cooperation, but it also avoids vendor lock-in and, additionally, saves time and cost. Although there is no established definition for Cloud interoperability, most researchers agree on the purposes of Cloud interoperability. Research and literature have attempted to explain interoperability as transferring data, moving workloads, and migrating virtual machines between Cloud platforms. Transferring data between Clouds refers to objects migrating between provider-specific domains. In comparison, data migration is the most commonly …

Correlation Between Air Quality Index And Traffic Volume Using Internet Of Things (Iot), Omar Sayah Alruwaili

Theses and Dissertations

In highly populated world areas, such as metropolises, hazardous air pollution has been linked to the presence of damaging climate and health issues, which are becoming increasingly common. Indeed, a major problem facing urban areas today is air pollution. Gas emissions from vehicles can be seen as the most important source of this kind of pollution. Pollutant gases emitted as parts of car exhaust consist of chemicals such as carbon monoxide (CO), nitrogen dioxide (NO2), and sulphur dioxide (SO2), and ozone (O3), as well as particulate matter (PM). In some places in the world, non-governmental and foreign corporations have also …

Analysing User Experience Of Mobile Banking Applications In Nigeria: A Text Mining Approach, Omotosho Babatunde S.

CBN Journal of Applied Statistics (JAS)

This paper analyses textual data mined from 37,460 reviews written by mobile banking application users in Nigeria over the period November 2012 – July 2020. On a scale of 1 to 5 (5 being the best), the average user rating for the twenty-two apps included in our sample is 3.5; with the apps deployed by non-interest banks having the highest average rating of 4.0 and those by commercial banks with national authorisation having the least rating of 3.4. Results from the sentiment analysis reveal that the share of positive sentiment words (17.8%) in the corpus more than double that of …

Emergency Landing And Guidance System, Joseph Alarid

Master's Theses

Every year there are thousands of aviation accidents along with hundreds of human deaths that happen around the world. While the data is sparse, it is well documented that many of these happen from emergency landings gone awry. While pilots can generally make great landings in clear daytime conditions, they are significantly handicapped when it comes to landing at night or amongst poor visibility conditions.

Due to the nature of this problem and some of the large scale advances in software technology we propose a solution that provides a significant improvement from the status quo. Using transfer learning on neural …

Docs_On_Blocks – A Defense In Depth Strategy For E-Healthcare, Saad Mohammed

Electronic Theses, Projects, and Dissertations

With the increase in the data breaches and cyber hacks, organizations have come to realize that cyber security alone would not help as the attacks are becoming more sophisticated and complex than ever. E-Healthcare industry has shown a promising improvement in terms of security over the past, but the threat remains. Thus, the E-Healthcare industries are aiming towards a Defense in Depth Strategy approach.

The project here describes how a Defense in Depth Strategy for E-Healthcare system can provide an environment for better security of the data and peer-to-peer interaction with stakeholders. The legacy systems have at some point failed …

Medical Knowledge-Enriched Textual Entailment Framework, Shweta Yadav, Vishal Pallagani, Amit P. Sheth

Publications

One of the cardinal tasks in achieving robust medical question answering systems is textual entailment. The existing approaches make use of an ensemble of pre-trained language models or data augmentation, often to clock higher numbers on the validation metrics. However, two major shortcomings impede higher success in identifying entailment: (1) understanding the focus/intent of the question and (2) ability to utilize the real-world background knowledge to capture the context beyond the sentence. In this paper, we present a novel Medical Knowledge-Enriched Textual Entailment framework that allows the model to acquire a semantic and global representation of the input medical text …

Deep Reinforcement Learning For Collaborative Edge Computing In Vehicular Networks, Mushu Li, Jie Gao, Lian Zhao, Xuemin Shen

Electrical and Computer Engineering Faculty Research and Publications

Mobile edge computing (MEC) is a promising technology to support mission-critical vehicular applications, such as intelligent path planning and safety applications. In this paper, a collaborative edge computing framework is developed to reduce the computing service latency and improve service reliability for vehicular networks. First, a task partition and scheduling algorithm (TPSA) is proposed to decide the workload allocation and schedule the execution order of the tasks offloaded to the edge servers given a computation offloading strategy. Second, an artificial intelligence (AI) based collaborative computing approach is developed to determine the task offloading, computing, and result delivery policy for vehicles. …

Onboard Autonomous Controllability Assessment For Fixed Wing Suavs, Brian Edward Duvall

Mechanical & Aerospace Engineering Theses & Dissertations

Traditionally fixed-wing small Unmanned Arial Vehicles (sUAV) are flown while in direct line of sight with commands from a remote operator. However, this is changing with the increased popularity and ready availability of low-cost flight controllers. Flight controllers provide fixed-wing sUAVs with functions that either minimize or eliminate the need for a remote operator. Since the remote operator is no longer controlling the sUAV, it is impossible to determine if the fixed-wing sUAV has proper control authority. In this work, a controllability detection system was designed, built, and flight-tested using COTS hardware. The method features in-situ measurement and analysis of …

Cyber Defense Remediation In Energy Delivery Systems, Kamrul Hasan

Computational Modeling & Simulation Engineering Theses & Dissertations

The integration of Information Technology (IT) and Operational Technology (OT) in Cyber-Physical Systems (CPS) has resulted in increased efficiency and facilitated real-time information acquisition, processing, and decision making. However, the increase in automation technology and the use of the internet for connecting, remote controlling, and supervising systems and facilities has also increased the likelihood of cybersecurity threats that can impact safety of humans and property. There is a need to assess cybersecurity risks in the power grid, nuclear plants, chemical factories, etc. to gain insight into the likelihood of safety hazards. Quantitative cybersecurity risk assessment will lead to informed cyber …

Parallelization Of The Advancing Front Local Reconnection Mesh Generation Software Using A Pseudo-Constrained Parallel Data Refinement Method, Kevin Mark Garner Jr.

Computer Science Theses & Dissertations

Preliminary results of a long-term project entailing the parallelization of an industrial strength sequential mesh generator, called Advancing Front Local Reconnection (AFLR), are presented. AFLR has been under development for the last 25 years at the NSF/ERC center at Mississippi State University. The parallel procedure that is presented is called Pseudo-constrained (PsC) Parallel Data Refinement (PDR) and consists of the following steps: (i) use an octree data-decomposition scheme to divide the original geometry into subdomains (octree leaves), (ii) refine each subdomain with the proper adjustments of its neighbors using the given refinement code, and (iii) combine all subdomain data into …

Framework For Reasoning With Speech Processing, Ahmed Laarfi

Theses and Dissertations

It is known that programming languages are textual. We try here to take the advantages of Speech Recognition (SR) and employ them in creating a verbal Language, which takes its instruction from the voice. Because this work is a novel approach in the programming world, we could not find any resources. This dissertation aims to make essential developments in Speech Recognition (SR)and Artificial Intelligence by constructing a new compiler that receives commands verbally and executes them. That means entering data into the Computer by voice commands. This method of input means that we link several major computer topics with several …

Modern Standard Arabic Speech Recognition: Using Formants Measurements To Extract Vowels From Arabic Words’ Consonant-Vowel-Consonant-Vowel Structure, Mohamed Ali Alshaari

Theses and Dissertations

Arabic texts suffer from missing diacritics (short vowels) which become obstacles for new learners. Speech Recognition is the translation of words spoken to text through intelligent computer programs. As of today, it has been integrated into many computer systems. Arabic Speech Recognition has made progress over the years, but it is still not as good as English speech recognition due to the problem of short vowels not being recognized. This is mainly because the Arabic language is unlike the English language in the nature because it is a Semitic language. This is reflected in different characteristics such as grammar, morphology, …

Efficient Edge Analytics: Addressing Cyber-Physical Masint With Machine Learning On Audio At The Edge, David Elliott

Theses and Dissertations

With the growth of the Internet of Things and the rise of Big Data, data processing and machine learning applications are being moved to cheap and low size, weight, and power (SWaP) devices at the edge, often in the form of mobile phones, embedded systems, or microcontrollers. The field of Cyber-Physical Measurements and Signature Intelligence (MASINT) makes use of these devices to analyze and exploit data in ways not otherwise possible, which results in increased data quality, increased security, and decreased bandwidth. However, methods to train and deploy models at the edge are limited, and models with sufficient accuracy are …

Software Development With Scrum: A Bibliometric Analysis And Profile, Peter Kokol, Sašo Zagoranski, Marko Kokol

Library Philosophy and Practice (e-journal)

Introduction of the Scrum approach into software engineering has changed the way software is being developed. The Scrum approach emphasizes the active end-user involvement, embracing of change, and /iterative delivery of products. Our study showed that Scrum has different variants or is used in combination with different methods. Some tools not normally used in the conventional software approaches, like gamification, content analysis and grounded theory are also employed. However, Scrum like other software development approach focuses on improvement of software process, software quality, business value, performance, usability and efficiency and at the same time to reduce cost, risk and uncertainty. …

Decentralized Event-Triggered Control In The Presence Of Adversaries, Paul Griffioen, Raffaele Romagnoli, Bruce H. Krogh, Bruce Sinopoli

Faculty Work Comprehensive List

Decentralized control systems are widely used in a number of situations and applications. In order for these systems to function properly and achieve their desired goals, information must be propagated between agents. However, communication between agents entails connecting to a network, potentially allowing adversaries to infiltrate the system through the network and attack multiple agents. To increase resiliency against these attacks, it is desirable for agents to operate disconnected from the network as much as possible, only communicating with other agents when it is absolutely necessary to achieve their goal or to maintain the safety of the overall system. This …

Pedagogy Of The Pandemic: A Case Study Of Emergency Remote Education In A Private Higher Education Institution In Egypt, Rania M Rafik Khalil, Shadia Fahim, Wadouda Badran, Hadia Fakhreldin, Maguid Hassan, Hani Ghali, Attia Attia, Sarah Khalil, Hassan Abdelhamid, Yasmine Abdel Moneim, Omar H. Karam

English Language and Literature

COVID19 caught almost every higher education institution off guard. The pandemic interrupted the teaching and learning process and required immediate implementation of emergency remote learning strategies. Teaching pedagogy turned to new ways of thinking about learning. Consequently, both academic staff and students had to adapt without warning to the challenges of teaching with advanced technology from home which was taking the world by storm. Overcoming this challenge in Egypt has been much easier for private universities in comparison to state universities because of the availability of facilities, funding, smaller cohorts and validation by partner western universities. This paper shares reflections …

Bibliometric Analysis Of Firefly Algorithm Applications In The Field Of Wireless Sensor Networks, Anupkumar M. Bongale Dr., Rahul Raghvendra Joshi Prof., Kalyani Dhananjay Kadam Prof.

Library Philosophy and Practice (e-journal)

Wireless Sensor Network is a network of wireless sensor nodes that are capable of sensing information from their surroundings and transmit the sensed information to data collection point known as a base station. Applications of wireless sensor networks are large in number and forest fire detection, landslide monitoring, etc. are few applications to note. The research challenges in wireless sensor networks is the transmission of data from the sensor node to the base station in an energy-efficient manner and network life prolongation. Cluster-based routing techniques are extensively adopted to address this research challenge. Researchers have used different metaheuristic and soft …