Mirai Bot Scanner Summation Prototype,
2019
Dakota State University
Mirai Bot Scanner Summation Prototype, Charles V. Frank Jr.
Masters Theses & Doctoral Dissertations
The Mirai botnet deploys a distributed mechanism with each Bot continually scanning for a potential new Bot Victim. A Bot continually generates a random IP address to scan the network for discovering a potential new Bot Victim. The Bot establishes a connection with the potential new Bot Victim with a Transmission Control Protocol (TCP) handshake. The Mirai botnet has recruited hundreds of thousands of Bots. With 100,000 Bots, Mirai Distributed Denial of Service (DDoS) attacks on service provider Dyn in October 2016 triggered the inaccessibility to hundreds of websites in Europe and North America (Sinanović & Mrdovic, 2017). A month …
A Theoretical Model Of Underground Dipole Antennas For Communications In Internet Of Underground Things,
2019
Purdue University
A Theoretical Model Of Underground Dipole Antennas For Communications In Internet Of Underground Things, Abdul Salam, Mehmet C. Vuran, Xin Dong, Christos Argyropoulos, Suat Irmak
Faculty Publications
The realization of Internet of Underground Things (IOUT) relies on the establishment of reliable communication links, where the antenna becomes a major design component due to the significant impacts of soil. In this paper, a theoretical model is developed to capture the impacts of change of soil moisture on the return loss, resonant frequency, and bandwidth of a buried dipole antenna. Experiments are conducted in silty clay loam, sandy, and silt loam soil, to characterize the effects of soil, in an indoor testbed and field testbeds. It is shown that at subsurface burial depths (0.1-0.4m), change in soil moisture impacts …
Smart Parking Systems Design And Integration Into Iot,
2019
University of Minnesota - Morris
Smart Parking Systems Design And Integration Into Iot, Charles M. Menne
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
This paper looks at two smart parking reservation algorithms, and examines the ongoing efforts to connect smart systems of different domains in a city's infrastructure. The reservation algorithms are designed to improve the performance of smart parking systems. The first algorithm considers the distance between parking areas and the number of free parking spaces in determining a parking space. The second algorithm uses distance between parking areas and driver destination, parking price, and the number of unoccupied spaces for each parking area. Neither of these smart parking systems cover how they could fit into a larger scale smart system. As …
Send Hardest Problems My Way: Probabilistic Path Prioritization For Hybrid Fuzzing,
2019
Singapore Management University
Send Hardest Problems My Way: Probabilistic Path Prioritization For Hybrid Fuzzing, Lei Zhao, Yue Duan, Jifeng Xuan
Research Collection School Of Computing and Information Systems
Hybrid fuzzing which combines fuzzing and concolic execution has become an advanced technique for software vulnerability detection. Based on the observation that fuzzing and concolic execution are complementary in nature, the state-of-the-art hybrid fuzzing systems deploy ``demand launch'' and ``optimal switch'' strategies. Although these ideas sound intriguing, we point out several fundamental limitations in them, due to oversimplified assumptions. We then propose a novel ``discriminative dispatch'' strategy to better utilize the capability of concolic execution. We design a novel Monte Carlo based probabilistic path prioritization model to quantify each path's difficulty and prioritize them for concolic execution. This model treats …
Bilateral Dependency Neural Networks For Cross-Language Algorithm Classification,
2019
Singapore Management University
Bilateral Dependency Neural Networks For Cross-Language Algorithm Classification, Duy Quoc Nghi Bui, Yijun Yu, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
Algorithm classification is to automatically identify the classes of a program based on the algorithm(s) and/or data structure(s) implemented in the program. It can be useful for various tasks, such as code reuse, code theft detection, and malware detection. Code similarity metrics, on the basis of features extracted from syntax and semantics, have been used to classify programs. Such features, however, often need manual selection effort and are specific to individual programming languages, limiting the classifiers to programs in the same language.To recognise the similarities and differences among algorithms implemented in different languages, this paper describes a framework of Bilateral …
A Sampling Approach For Proactive Project Scheduling Under Generalized Time-Dependent Workability Uncertainty,
2019
Singapore Management University
A Sampling Approach For Proactive Project Scheduling Under Generalized Time-Dependent Workability Uncertainty, Wen Song, Donghun Kang, Jie Zhang, Zhiguang Cao, Hui Xi
Research Collection School Of Computing and Information Systems
In real-world project scheduling applications, activity durations are often uncertain. Proactive scheduling can effectively cope with the duration uncertainties, by generating robust baseline solutions according to a priori stochastic knowledge. However, most of the existing proactive approaches assume that the duration uncertainty of an activity is not related to its scheduled start time, which may not hold in many real-world scenarios. In this paper, we relax this assumption by allowing the duration uncertainty to be time-dependent, which is caused by the uncertainty of whether the activity can be executed on each time slot. We propose a stochastic optimization model to …
Dish: Democracy In State Houses,
2019
California Polytechnic State University, San Luis Obispo
Dish: Democracy In State Houses, Nicholas A. Russo
Master's Theses
In our current political climate, state level legislators have become increasingly impor- tant. Due to cuts in funding and growing focus at the national level, public oversight for these legislators has drastically decreased. This makes it difficult for citizens and activists to understand the relationships and commonalities between legislators. This thesis provides three contributions to address this issue. First, we created a data set containing over 1200 features focused on a legislator’s activity on bills. Second, we created embeddings that represented a legislator’s level of activity and engagement for a given bill using a custom model called Democracy2Vec. Third, we …
Improving Vix Futures Forecasts Using Machine Learning Methods,
2019
Southern Methodist University
Improving Vix Futures Forecasts Using Machine Learning Methods, James Hosker, Slobodan Djurdjevic, Hieu Nguyen, Robert Slater
SMU Data Science Review
The problem of forecasting market volatility is a difficult task for most fund managers. Volatility forecasts are used for risk management, alpha (risk) trading, and the reduction of trading friction. Improving the forecasts of future market volatility assists fund managers in adding or reducing risk in their portfolios as well as in increasing hedges to protect their portfolios in anticipation of a market sell-off event. Our analysis compares three existing financial models that forecast future market volatility using the Chicago Board Options Exchange Volatility Index (VIX) to six machine/deep learning supervised regression methods. This analysis determines which models provide best …
A Comparative Evaluation Of Recommender Systems For Hotel Reviews,
2019
Southern Methodist University
A Comparative Evaluation Of Recommender Systems For Hotel Reviews, Ryan Khaleghi, Kevin Cannon, Raghuram Srinivas
SMU Data Science Review
There has been increasing growth in deployment of recommender systems across Internet sites, with various models being used. These systems have been particularly valuable for review sites, as they seek to add value to the user experience to gain market share and to create new revenue streams through deals. Hotels are a prime target for this effort, as there is a large number for most destinations and a lot of differentiation between them. In this paper, we present an evaluation of two of the most popular methods for hotel review recommender systems: collaborative filtering and matrix factorization. The accuracy of …
A Machine Learning Recommender Model For Ride Sharing Based On Rider Characteristics And User Threshold Time,
2019
Marshall University
A Machine Learning Recommender Model For Ride Sharing Based On Rider Characteristics And User Threshold Time, Govind Pramod Yatnalkar
Theses, Dissertations and Capstones
In the present age, human life is prospering incredibly due to the 4th Industrial Revolution or The Age of Digitization and Computing. The ubiquitous availability of the Internet and advanced computing systems have resulted in the rapid development of smart cities. From connected devices to live vehicle tracking, technology is taking the field of transportation to a new level. An essential part of the transportation domain in smart cities is Ride Sharing. It is an excellent solution to issues like pollution, traffic, and the rapid consumption of fuel. Even though Ride Sharing has several benefits, the current usage is …
Radically Simplifying Gated Recurrent Architectures Without Loss Of Performance,
2019
Kennesaw State University
Radically Simplifying Gated Recurrent Architectures Without Loss Of Performance, Jonathan Boardman, Ying Xie
Published and Grey Literature from PhD Candidates
Long Short-Term Memory (LSTM) units are a family of Recurrent Neural Network (RNN) architectures that have proven incredibly effective at learning from sequence data. They are also extremely complex, making them expensive to train and difficult to understand. A recent trend towards simplification has produced the Gated Recurrent Unit (GRU) and the Minimal Gated Unit (MGU), both of which perform as well as the LSTM (or better) on a variety of tasks. The MGU is one of the simplest gated recurrent architectures at the moment. Our study demonstrates that it is possible to radically simplify the MGU without significant loss …
Squared Distance Matrix Of A Weighted Tree,
2019
Indian Statistical Institute (Delhi Centre)
Squared Distance Matrix Of A Weighted Tree, Ravindra B. Bapat
Journal Articles
Let T be a tree with vertex set f1;: :: ; ng such that each edge is assigned a nonzero weight. The squared distance matrix of T; denoted by is the n n matrix with (i; j)-element d(i; j)2; where d(i; j) is the sum of the weights of the edges on the (ij)-path. We obtain a formula for the determinant of A formula for 1 is also obtained, under certain conditions. The results generalize known formulas for the unweighted case.
Statistical Analysis Of Tandem Queues With Markovian Passages In Porous Mediums,
2019
Marshall University
Statistical Analysis Of Tandem Queues With Markovian Passages In Porous Mediums, Gboyega David Adepoju
Theses, Dissertations and Capstones
Queuing theory is the mathematical study of queues or waiting lines. A queue is formed whenever the demand for service exceeds the capacity to provide service at that point in time. In this thesis, the birth-and-death process is used to model the movement of customers or units into and out of a network of queues in tandem. We start with the theoretical analysis of M/M/1 queues with Poisson arrival and exponential service time with first-come first-served (FCFS) discipline and one service station. We derive the global balance equation for each network. Using both the iterative and the probability generating function, …
Android Application For Mnist Handwritten Digits Classification,
2019
Harrisburg University of Science and Technology
Android Application For Mnist Handwritten Digits Classification, Mina Gabriel
Project Topics and Ideas
Use Neural Network architecture to classify MNIST handwritten digits dataset, student/s should implement a phone application (Android) to demonstrate their work, application will then be published to the app store for other students and CISC faculty members for evaluation and feedback.
Optimal Gateway Placement In Low-Cost Smart Cities,
2019
University of Kentucky
Optimal Gateway Placement In Low-Cost Smart Cities, Oluwashina Madamori
Theses and Dissertations--Computer Science
Rapid urbanization burdens city infrastructure and creates the need for local governments to maximize the usage of resources to serve its citizens. Smart city projects aim to alleviate the urbanization problem by deploying a vast amount of Internet-of-things (IoT) devices to monitor and manage environmental conditions and infrastructure. However, smart city projects can be extremely expensive to deploy and manage partly due to the cost of providing Internet connectivity via 5G or WiFi to IoT devices. This thesis proposes the use of delay tolerant networks (DTNs) as a backbone for smart city communication; enabling developing communities to become smart cities …
High Dimensional Outlier Detection,
2019
University of Montana
High Dimensional Outlier Detection, Omid Khormali
Graduate Student Theses, Dissertations, & Professional Papers
In statistics and data science, outliers are data points that differ greatly from other observations in a data set. They are important attributes of the data because they can dramatically influence patterns and relationships manifested by non-outliers. It is therefore very important to detect and adequately deal with outliers. Recently, a novel algorithm, the ROMA algorithm, has been proposed [11]. In this paper, we propose a modification of the ROMA algorithm that reduces its computational complexity from $O(n^2 m)$ to $O((n/(2^m-o(1)))^2 m)$ where $n$ is the number of data points and $m$ is the dimension of the space. And as …
Development Of A Sensing System For Underground Optic Fiber Cable Conduit Mapping,
2019
Minnesota State University, Mankato
Development Of A Sensing System For Underground Optic Fiber Cable Conduit Mapping, Sherif Bakr
All Graduate Theses, Dissertations, and Other Capstone Projects
The motivation of this research is to obtain an accurate three-dimensional (3D) layout of an underground conduit, which may be beneficial to optic fiber cable installers and engineers. A newly designed algorithm for 3D position tracking with the help of an inertial sensor and an encoder has been developed. Two types of representations (Euler angle and Quaternion) for orientation and rotation are also introduced, followed by several data pre-processing procedures. A sensing fusion method is utilized to overcome the accumulated errors introduced by the sensor drifting. Considering the application of 3D underground duct mapping in this research, a sensing system …
Modeling Stochastically Intransitive Relationships In Paired Comparison Data,
2019
Southern Methodist University
Modeling Stochastically Intransitive Relationships In Paired Comparison Data, Ryan Patrick Alexander Mcshane
Statistical Science Theses and Dissertations
If the Warriors beat the Rockets and the Rockets beat the Spurs, does that mean that the Warriors are better than the Spurs? Sophisticated fans would argue that the Warriors are better by the transitive property, but could Spurs fans make a legitimate argument that their team is better despite this chain of evidence?
We first explore the nature of intransitive (rock-scissors-paper) relationships with a graph theoretic approach to the method of paired comparisons framework popularized by Kendall and Smith (1940). Then, we focus on the setting where all pairs of items, teams, players, or objects have been compared to …
Analyzing Satisfiability And Refutability In Selected Constraint Systems,
2019
West Virginia University
Analyzing Satisfiability And Refutability In Selected Constraint Systems, Piotr Jerzy Wojciechowski
Graduate Theses, Dissertations, and Problem Reports (ETD)
This dissertation is concerned with the satisfiability and refutability problems for several constraint systems. We examine both Boolean constraint systems, in which each variable is limited to the values true and false, and polyhedral constraint systems, in which each variable is limited to the set of real numbers R in the case of linear polyhedral systems or the set of integers Z in the case of integer polyhedral systems. An important aspect of our research is that we focus on providing certificates. That is, we provide satisfying assignments or easily checkable proofs of infeasibility depending on whether the instance …
Object-Based Supervised Machine Learning Regional-Scale Land-Cover Classification Using High Resolution Remotely Sensed Data,
2019
West Virginia University
Object-Based Supervised Machine Learning Regional-Scale Land-Cover Classification Using High Resolution Remotely Sensed Data, Christopher A. Ramezan
Graduate Theses, Dissertations, and Problem Reports (ETD)
High spatial resolution (HR) (1m – 5m) remotely sensed data in conjunction with supervised machine learning classification are commonly used to construct land-cover classifications. Despite the increasing availability of HR data, most studies investigating HR remotely sensed data and associated classification methods employ relatively small study areas. This work therefore drew on a 2,609 km2, regional-scale study in northeastern West Virginia, USA, to investigates a number of core aspects of HR land-cover supervised classification using machine learning. Issues explored include training sample selection, cross-validation parameter tuning, the choice of machine learning algorithm, training sample set size, and feature selection. A …
