Self-Supervised Learning To Detect Key Frames In Videos, 2020 Edith Cowan University
Self-Supervised Learning To Detect Key Frames In Videos, Xiang Yan, Syed Zulqarnain Gilani, Mingtao Feng, Liang Zhang, Hanlin Qin, Ajmal Mian
ECU Publications Post 2013
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Detecting key frames in videos is a common problem in many applications such as video classification, action recognition and video summarization. These tasks can be performed more efficiently using only a handful of key frames rather than the full video. Existing key frame detection approaches are mostly designed for supervised learning and require manual labelling of key frames in a large corpus of training data to train the models. Labelling requires human annotators from different backgrounds to annotate key frames in videos which is not only expensive and time consuming but also ...
An Approach To System Of Systems Resiliency Using Architecture And Agent-Based Behavioral Modeling, 2020 Missouri University of Science and Technology
An Approach To System Of Systems Resiliency Using Architecture And Agent-Based Behavioral Modeling, Paulette Bootz Acheson
”In today’s world it is no longer a question of whether a system will be compromised but when the system will be compromised. Consider the recent compromise of the Democratic National Committee (DNC) and Hillary Clinton emails as well as the multiple Yahoo breaches and the break into the Target customer database. The list of exploited vulnerabilities and successful cyber-attacks goes on and on. Because of the amount and frequency of the cyber-attacks, resiliency has taken on a whole new meaning. There is a new perspective within defense to consider resiliency in terms of Mission Success.
This research develops ...
Digitalization In Practice: The Fifth Discipline Advantage, 2019 Singapore Management University
Digitalization In Practice: The Fifth Discipline Advantage, Siu Loon Hoe
Research Collection School Of Computing and Information Systems
Purpose The purpose of this paper is to provide advice to organizations on how to become successful in the digital age. The paper revisits Peter Senge's (1990) notion of the learning organization and discusses the relevance of systems thinking and the other four disciplines, namely, personal mastery, mental models, shared vision and team learning in the context of the current digitalization megatrend. Design/methodology/approach This paper is based on content analysis of essays from international organizations, strategy experts and management scholars, and insights gained from the author's consulting experience. A comparative case study from the health and ...
Contrasting Geometric Variations Of Mathematical Models Of Self-Assembling Systems, 2019 University of Arkansas, Fayetteville
Contrasting Geometric Variations Of Mathematical Models Of Self-Assembling Systems, Michael Sharp
Graduate Theses and Dissertations
Self-assembly is the process by which complex systems are formed and behave due to the interactions of relatively simple units. In this thesis, we explore multiple augmentations of well known models of self-assembly to gain a better understanding of the roles that geometry and space play in their dynamics. We begin in the abstract Tile Assembly Model (aTAM) with some examples and a brief survey of previous results to provide a foundation. We then introduce the Geometric Thermodynamic Binding Network model, a model that focuses on the thermodynamic stability of its systems while utilizing geometrically rigid components (dissimilar to other ...
Countering Cybersecurity Vulnerabilities In The Power System, 2019 University of Arkansas, Fayetteville
Countering Cybersecurity Vulnerabilities In The Power System, Fengli Zhang
Graduate Theses and Dissertations
Security vulnerabilities in software pose an important threat to power grid security, which can be exploited by attackers if not properly addressed. Every month, many vulnerabilities are discovered and all the vulnerabilities must be remediated in a timely manner to reduce the chance of being exploited by attackers. In current practice, security operators have to manually analyze each vulnerability present in their assets and determine the remediation actions in a short time period, which involves a tremendous amount of human resources for electric utilities. To solve this problem, we propose a machine learning-based automation framework to automate vulnerability analysis and ...
On The Yellow Brick Road, A Path To Enterprise Architecture Maturity, 2019 University of the Witwatersrand
On The Yellow Brick Road, A Path To Enterprise Architecture Maturity, Avsharn Bachoo
The African Journal of Information Systems
This study concentrated on the relationship between the Enterprise Architecture (EA) maturity of an organization and the business value associated with it in the South African financial services environment. It was developed within the critical realism philosophy, which states that mechanisms generate events by accentuating the underlying EA mechanisms that lead to business value, as well as provide insights into the opportunities and challenges organizations experienced as they progressed to higher levels of maturity. Constructed using the resource-based view of the firm as the underlying theoretical framework, this research examined EA as an intangible resource and maturity as a source ...
Similarity-Based Chained Transfer Learning For Energy Forecasting With Big Data, 2019 Western University
Similarity-Based Chained Transfer Learning For Energy Forecasting With Big Data, Yifang Tian, Ljubisa Sehovac, Katarina Grolinger
Electrical and Computer Engineering Publications
Smart meter popularity has resulted in the ability to collect big energy data and has created opportunities for large-scale energy forecasting. Machine Learning (ML) techniques commonly used for forecasting, such as neural networks, involve computationally intensive training typically with data from a single building or a single aggregated load to predict future consumption for that same building or aggregated load. With hundreds of thousands of meters, it becomes impractical or even infeasible to individually train a model for each meter. Consequently, this paper proposes Similarity-Based Chained Transfer Learning (SBCTL), an approach for building neural network-based models for many meters by ...
Extract Transform And Loading Tool For Email, 2019 California State University – San Bernardino
Extract Transform And Loading Tool For Email, Amit Rajiv Lawanghare
Electronic Theses, Projects, and Dissertations
This project focuses on applying Extract, Transform and Load (ETL) operations on the relational data exchanged via emails. An Email is an important form of communication by both personal and corporate means as it enables reliable and quick exchange. Many useful files are shared as a form of attachments which contains transactional/ relational data. This tool allows a user to write the filter conditions and lookup conditions on attachments; define the attribute map for attachments to the database table. The Data Cleansing for each attribute can be performed writing rules and their matching state. A user can add custom functions ...
Formally Designing And Implementing Cyber Security Mechanisms In Industrial Control Networks., 2019 University of Louisville
Formally Designing And Implementing Cyber Security Mechanisms In Industrial Control Networks., Mehdi Sabraoui
Electronic Theses and Dissertations
This dissertation describes progress in the state-of-the-art for developing and deploying formally verified cyber security devices in industrial control networks. It begins by detailing the unique struggles that are faced in industrial control networks and why concepts and technologies developed for securing traditional networks might not be appropriate. It uses these unique struggles and examples of contemporary cyber-attacks targeting control systems to argue that progress in securing control systems is best met with formal verification of systems, their specifications, and their security properties. This dissertation then presents a development process and identifies two technologies, TLA+ and seL4, that can be ...
Trust Architecture And Reputation Evaluation For Internet Of Things, 2019 Singapore Management University
Trust Architecture And Reputation Evaluation For Internet Of Things, Juan Chen, Zhihong Tian, Xiang Cui, Lihua Yin, Xianzhi Wang
Research Collection School Of Computing and Information Systems
Internet of Things (IoT) represents a fundamental infrastructure and set of techniques that support innovative services in various application domains. Trust management plays an important role in enabling the reliable data collection and mining, context-awareness, and enhanced user security in the IoT. The main tasks of trust management include trust architecture design and reputation evaluation. However, existing trust architectures and reputation evaluation solutions cannot be directly applied to the IoT, due to the large number of physical entities, the limited computation ability of physical entities, and the highly dynamic nature of the network. In comparison, it generally requires a general ...
Teaching Self-Balancing Trees Using A Beauty Contest, 2019 Sacred Heart University
Teaching Self-Balancing Trees Using A Beauty Contest, Samah Senbel
School of Computer Science & Engineering Faculty Publications
Trees data structures and their performance is one of the main topics to teach in a data structures course. Appreciating the importance of tree structure and tree height in software performance is an important concept to teach. In this paper, a simple and amusing activity is presented. It demonstrates to students the importance of a well-balanced tree by comparing the height of a binary search tree to a balanced (AVL) tree build upon some personal data to find the “prettiest” tree (minimum height). The activity highlights the fact that, irrelevant of your data sequence, a balanced tree guarantees a height ...
An Architecture For Blockchain-Based Collaborative Signature-Based Intrusion Detection System, 2019 Kennesaw State University
An Architecture For Blockchain-Based Collaborative Signature-Based Intrusion Detection System, Daniel Laufenberg
Master of Science in Information Technology Theses
Collaborative intrusion detection system (CIDS), where IDS hosts work with each other and share resources, have been proposed to cope with the increasingly sophisticated cyberattacks. Despite the promising benefits such as expanded signature databases and alert data from multiple sites, trust management and consensus building remain as challenges for a CIDS to work effectively. The blockchain technology with built-in immutability and consensus building capability provides a viable solution to the issues of CIDS. In this paper, we introduce an architecture for a blockchain-enabled signature-based collaborative IDS, discuss the implementation strategy of the proposed architecture and developed a prototype using Hyperledger ...
Sensitive Behavior Analysis Of Android Applications On Unrooted Devices In The Wild, 2019 Singapore Management University
Sensitive Behavior Analysis Of Android Applications On Unrooted Devices In The Wild, Xiaoxiao Tang
Dissertations and Theses Collection (Open Access)
Dynamic analysis is widely used in malware detection, taint analysis, vulnerability detection, and other areas for enhancing the security of Android. Compared to static analysis, dynamic analysis is immune to common code obfuscation techniques and dynamic code loading. Existing dynamic analysis techniques rely on in-lab running environment (e.g., modified systems, rooted devices, or emulators) and require automatic input generators to execute the target app. However, these techniques could be bypassed by anti-analysis techniques that allow apps to hide sensitive behavior when an in-lab environment is detected through predefined heuristics (e.g., IMEI number of the device is invalid). Meanwhile ...
Uncomplicating The Business Of Repositories, 2019 University of Pennsylvania
Uncomplicating The Business Of Repositories, Kate Lynch, Emily Morton-Owens
Scholarship at Penn Libraries
In this presentation, we discuss how our library runs our repository in production to meet the needs of our “business” as efficiently as possible. We have an interest in limiting the number of digital platforms we manage, for the purposes of sustainability and efficiency, but we must also consider how well a general platform can meet specific user needs.
A governance group of administrators, in conference with stakeholders and developers, seeks to find the best way to accommodate each collection or functional need, with an eye to minimizing technical complexity, offering stakeholders self-serve options when possible, and maintaining a single ...
The Performance Cost Of Security, 2019 California Polytechnic State University, San Luis Obispo
The Performance Cost Of Security, Lucy R. Bowen
Historically, performance has been the most important feature when optimizing computer hardware. Modern processors are so highly optimized that every cycle of computation time matters. However, this practice of optimizing for performance at all costs has been called into question by new microarchitectural attacks, e.g. Meltdown and Spectre. Microarchitectural attacks exploit the effects of microarchitectural components or optimizations in order to leak data to an attacker. These attacks have caused processor manufacturers to introduce performance impacting mitigations in both software and silicon.
To investigate the performance impact of the various mitigations, a test suite of forty-seven different tests was ...
Virtual Sensor Middleware: A Middleware For Managing Iot Data For The Fog-Cloud Platform, 2019 The University of Western Ontario
Virtual Sensor Middleware: A Middleware For Managing Iot Data For The Fog-Cloud Platform, Fadi Almahamid
Electronic Thesis and Dissertation Repository
Internet of Things is a massively growing field where billions of devices are connected to the Internet using different protocols and produce an enormous amount of data. The produced data is consumed and processed by different applications to make operations more efficient. Application development is challenging, especially when applications access sensor data since IoT devices use different communication protocols.
The existing IoT architectures address some of these challenges. This thesis proposes an IoT Middleware that provides applications with the abstraction required of IoT devices while distributing the processing of sensor data to provide a real-time or near real-time response and ...
Mobile Music Development Tools For Creative Coders, 2019 Louisiana State University and Agricultural and Mechanical College
Mobile Music Development Tools For Creative Coders, Daniel Stuart Holmes
LSU Doctoral Dissertations
This project is a body of work that facilitates the creation of musical mobile artworks. The project includes a code toolkit that enhances and simplifies the development of mobile music iOS applications, a flexible notation system designed for mobile musical interactions, and example apps and scored compositions to demonstrate the toolkit and notation system.
The code library is designed to simplify the technical aspect of user-centered design and development with a more direct connection between concept and deliverable. This sim- plification addresses learning problems (such as motivation, self-efficacy, and self-perceived understanding) by bridging the gap between idea and functional prototype ...
Real-Time Data Processing With Lambda Architecture, 2019 San Jose State University
Real-Time Data Processing With Lambda Architecture, Omkar Ashok Malusare
Data has evolved immensely in recent years, in type, volume and velocity. There are several frameworks to handle the big data applications. The project focuses on the Lambda Architecture proposed by Marz and its application to obtain real-time data processing. The architecture is a solution that unites the benefits of the batch and stream processing techniques. Data can be historically processed with high precision and involved algorithms without loss of short-term information, alerts and insights. Lambda Architecture has an ability to serve a wide range of use cases and workloads that withstands hardware and human mistakes. The layered architecture enhances ...
A Study Of The Effect Of Memory System Configuration On The Power Consumption Of An Fpga Processor, 2019 James Madison University
A Study Of The Effect Of Memory System Configuration On The Power Consumption Of An Fpga Processor, Adam Blalock
Senior Honors Projects, 2010-2019
With electrical energy being a finite resource, feasible methods of reducing system power consumption continue to be of great importance within the field of computing, especially as computers proliferate. A victim cache is a small fully associative cache that “captures” lines evicted from L1 cache memory, thereby reducing lower memory accesses and compensating for conflict misses. Little experimentation has been done to evaluate its effect on system power behavior and consumption. This project investigates the performance and power consumption of three different processor memory designs for a sample program using a field programmable gate array (FPGA) and the Vivado Integrated ...
Visualization And Machine Learning Techniques For Nasa’S Em-1 Big Data Problem, 2019 Southern Methodist University
Visualization And Machine Learning Techniques For Nasa’S Em-1 Big Data Problem, Antonio P. Garza Iii, Jose Quinonez, Misael Santana, Nibhrat Lohia
SMU Data Science Review
In this paper, we help NASA solve three Exploration Mission-1 (EM-1) challenges: data storage, computation time, and visualization of complex data. NASA is studying one year of trajectory data to determine available launch opportunities (about 90TBs of data). We improve data storage by introducing a cloud-based solution that provides elasticity and server upgrades. This migration will save $120k in infrastructure costs every four years, and potentially avoid schedule slips. Additionally, it increases computational efficiency by 125%. We further enhance computation via machine learning techniques that use the classic orbital elements to predict valid trajectories. Our machine learning model decreases trajectory ...