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Morphogenesis And Growth Driven By Selection Of Dynamical Properties, Yuri Cantor 2017 The Graduate Center, City University of New York

Morphogenesis And Growth Driven By Selection Of Dynamical Properties, Yuri Cantor

All Graduate Works by Year: Dissertations, Theses, and Capstone Projects

Organisms are understood to be complex adaptive systems that evolved to thrive in hostile environments. Though widely studied, the phenomena of organism development and growth, and their relationship to organism dynamics is not well understood. Indeed, the large number of components, their interconnectivity, and complex system interactions all obscure our ability to see, describe, and understand the functioning of biological organisms.

Here we take a synthetic and computational approach to the problem, abstracting the organism as a cellular automaton. Such systems are discrete digital models of real-world environments, making them more accessible and easier to study then their physical world ...


Operating System Identification By Ipv6 Communication Using Machine Learning Ensembles, Adrian Ordorica 2017 University of Arkansas, Fayetteville

Operating System Identification By Ipv6 Communication Using Machine Learning Ensembles, Adrian Ordorica

Theses and Dissertations

Operating system (OS) identification tools, sometimes called fingerprinting tools, are essential for the reconnaissance phase of penetration testing. While OS identification is traditionally performed by passive or active tools that use fingerprint databases, very little work has focused on using machine learning techniques. Moreover, significantly more work has focused on IPv4 than IPv6. We introduce a collaborative neural network ensemble that uses a unique voting system and a random forest ensemble to deliver accurate predictions. This approach uses IPv6 features as well as packet metadata features for OS identification. Our experiment shows that our approach is valid and we achieve ...


Transaction Cost Optimization For Online Portfolio Selection, Bin LI, Jialei WANG, Dingjiang HUANG, Steven C. H. HOI 2017 Singapore Management University

Transaction Cost Optimization For Online Portfolio Selection, Bin Li, Jialei Wang, Dingjiang Huang, Steven C. H. Hoi

Research Collection School Of Information Systems

To improve existing online portfolio selection strategies in the case of non-zero transaction costs, we propose a novel framework named Transaction Cost Optimization (TCO). The TCO framework incorporates the L1 norm of the difference between two consecutive allocations together with the principles of maximizing expected log return. We further solve the formulation via convex optimization, and obtain two closed-form portfolio update formulas, which follow the same principle as Proportional Portfolio Rebalancing (PPR) in industry. We empirically evaluate the proposed framework using four commonly used data-sets. Although these data-sets do not consider delisted firms and are thus subject to survival bias ...


Automated Android Application Permission Recommendation, Lingfeng BAO, David LO, Xin XIA 2017 Singapore Management University

Automated Android Application Permission Recommendation, Lingfeng Bao, David Lo, Xin Xia

Research Collection School Of Information Systems

The number of Android applications has increased rapidly as Android is becoming the dominant platform in the smartphone market. Security and privacy are key factors for an Android application to be successful. Android provides a permission mechanism to ensure security and privacy. This permission mechanism requires that developers declare the sensitive resources required by their applications. On installation or during runtime, users are required to agree with the permission request. However, in practice, there are numerous popular permission misuses, despite Android introducing official documents stating how to use these permissions properly. Some data mining techniques (e.g., association rule mining ...


Tlel: A Two-Layer Ensemble Learning Approach For Just-In-Time Defect Prediction, Xinli YANG, David LO, Xin XIA, Jianling SUN 2017 Singapore Management University

Tlel: A Two-Layer Ensemble Learning Approach For Just-In-Time Defect Prediction, Xinli Yang, David Lo, Xin Xia, Jianling Sun

Research Collection School Of Information Systems

Context:Defect prediction is a very meaningful topic, particularly at change-level. Change-level defectprediction, which is also referred as just-in-time defect prediction, could not only ensure software qualityin the development process, but also make the developers check and fix the defects in time [1].Objective: Ensemble learning becomes a hot topic in recent years. There have been several studies aboutapplying ensemble learning to defect prediction [2–5]. Traditional ensemble learning approaches onlyhave one layer, i.e., they use ensemble learning once. There are few studies that leverages ensemblelearning twice or more. To bridge this research gap, we try to hybridize various ...


Discovering Explanatory Models To Identify Relevant Tweets On Zika, RoopTeja Muppalla, Michele Miller, Tanvi Banerjee, William L. Romine 2017 Wright State University - Main Campus

Discovering Explanatory Models To Identify Relevant Tweets On Zika, Roopteja Muppalla, Michele Miller, Tanvi Banerjee, William L. Romine

Kno.e.sis Publications

Zika virus has caught the worlds attention, and has led people to share their opinions and concerns on social media like Twitter. Using text-based features, extracted with the help of Parts of Speech (POS) taggers and N-gram, a classifier was built to detect Zika related tweets from Twitter. With a simple logistic classifier, the system was successful in detecting Zika related tweets from Twitter with a 92% accuracy. Moreover, key features were identified that provide deeper insights on the content of tweets relevant to Zika. This system can be leveraged by domain experts to perform sentiment analysis, and understand the ...


A Knowledge Graph Framework For Detecting Traffic Events Using Stationary Cameras, RoopTeja Muppalla, Sarasi Lalithsena, Tanvi Banerjee, Amit Sheth 2017 Wright State University - Main Campus

A Knowledge Graph Framework For Detecting Traffic Events Using Stationary Cameras, Roopteja Muppalla, Sarasi Lalithsena, Tanvi Banerjee, Amit Sheth

Kno.e.sis Publications

With the rapid increase in urban development, it is critical to utilize dynamic sensor streams for traffic understanding, especially in larger cities where route planning or infrastructure planning is more critical. This creates a strong need to understand traffic patterns using ubiquitous sensors to allow city officials to be better informed when planning urban construction and to provide an understanding of the traffic dynamics in the city. In this study, we propose our framework ITSKG (Imagery-based Traffic Sensing Knowledge Graph) which utilizes the stationary traffic camera information as sensors to understand the traffic patterns. The proposed system extracts image-based features ...


Quo Vadis-A Framework For Intelligent Routing In Large Communication Networks., Armin Mikler, Johnny S. Wong, Vasant Honavar 2017 Iowa State University

Quo Vadis-A Framework For Intelligent Routing In Large Communication Networks., Armin Mikler, Johnny S. Wong, Vasant Honavar

Johnny Wong

This paper presents Quo Vadis, an evolving framework for intelligent traffic management in very large communication networks. Quo Vadis is designed to exploit topological properties of large networks as well as their spatio-temporal dynamics to optimize multiple performance criteria through cooperation among nodes in the network. It employs a distributed representation of network state information using local load measurements supplemented by a less precise global summary. Routing decisions in Quo Vadis are based on parameterized heuristics designed to optimize various performance metrics in an anticipatory or pro-active as well as compensatory or reactive mode and to minimize the overhead associated ...


An Object Oriented Approach To Modeling And Simulation Of Routing In Large Communication Networks, Armin Mikler, Johnny S. Wong, Vasant Honavar 2017 Iowa State University

An Object Oriented Approach To Modeling And Simulation Of Routing In Large Communication Networks, Armin Mikler, Johnny S. Wong, Vasant Honavar

Johnny Wong

The complexity (number of entities, interactions between entities, and resulting emergent dynamic behavior) of large communication environments which contain hundreds of nodes and links make simulation an important tool for the study of such systems. Given the difficulties associated with complete analytical treatment of complex dynamical systems, it is often the only practical tool that is available. This paper presents an example of a flexible, modular, object-oriented toolbox designed to support modeling and experimental analysis of a large family of heuristic knowledge representation and decision functions for adaptive self-managing communication networks with particular emphasis on routing strategies. It discusses in ...


Feature Selection In Intrusion Detection System Over Mobile Ad-Hoc Network, Xia Wang, Tu-liang Lin, Johnny S. Wong 2017 Iowa State University

Feature Selection In Intrusion Detection System Over Mobile Ad-Hoc Network, Xia Wang, Tu-Liang Lin, Johnny S. Wong

Johnny Wong

As Mobile ad-hoc network (MANET) has become a very important technology the security problem, especially, intrusion detection technique research has attracted many people�s effort. MANET is more vulnerable than wired network and suffers intrusion like wired network. This paper investigated some intrusion detection techniques using machine learning and proposed a profile based neighbor monitoring intrusion detection method. Further analysis shows that the features collected by each node are too many for wireless devices with limited capacity. We apply Markov Blanket algorithm [1] to the feature selection of the intrusion detection method. Experimental studies have shown that Markov Blanket algorithm ...


Quo Vadis - Adaptive Heuristics For Routing In Large Communication Networks, Armin Mikler, Johnny S. Wong, Vasant Honavar 2017 Iowa State University

Quo Vadis - Adaptive Heuristics For Routing In Large Communication Networks, Armin Mikler, Johnny S. Wong, Vasant Honavar

Johnny Wong

This paper presents Quo Vadis, an evolving framework for intelligent traffic management in very large communication networks. Quo Vadis is designed to exploit topological properties of large networks as well as their spatio-temporal dynamics to optimize multiple performance criteria through cooperation among nodes in the network. It employs a distributed representation of network state information using local load measurements supplemented by a less precise global summary. Routing decisions in Quo Vadis are based on parameterized heuristics designed to optimize various performance metrics in an anticipatory or pro-active as well as compensatory or reactive mode and to minimize the overhead associated ...


The Methodology For Evaluating Response Cost For Intrusion Response Systems, Christopher Roy Strasburg, Natalia Stakhanova, Samik Basu, Johnny S. Wong 2017 Iowa State University

The Methodology For Evaluating Response Cost For Intrusion Response Systems, Christopher Roy Strasburg, Natalia Stakhanova, Samik Basu, Johnny S. Wong

Johnny Wong

Recent advances in the field of intrusion detection brought new requirements to intrusion prevention and response. Traditionally, the response to the detected attack was selected and deployed manually, in the recent years the focus has shifted towards developing automated and semi-automated methodologies for responding to intrusions. In this context, the cost-sensitive intrusion response models have gained the most interest mainly due to their emphasis on the balance between potential damage incurred by the intrusion and cost of the response. However, one of the challenges in applying this approach is defining consistent and adaptable measurement of these cost factors on the ...


Specification Synthesis For Monitoring And Analysis Of Manet Protocols, Natalia Stakhanova, Samik Basu, Zhang Wensheng, Xia Wang, Johnny S. Wong 2017 Iowa State University

Specification Synthesis For Monitoring And Analysis Of Manet Protocols, Natalia Stakhanova, Samik Basu, Zhang Wensheng, Xia Wang, Johnny S. Wong

Johnny Wong

This paper introduces an approach to automatic synthesis of the specification models of rout- ing protocol behavior from the observed flow of the network traffic. In particular, our technique generalizes the monitored sequences of routing messages constructing a high-level abstract view of the protocol. The basis of our method is similar to Inductive Logic Programming technique that derives a sound hypothesis from the individual examples. We conduct preliminary experi- ments on the example of AODV and DSR ad-hoc routing protocols and discuss the effectiveness of the generated specification models in detecting protocol misuses.


Utility-Theoretic Heuristics For Intelligent Adaptive Routing In Large Communcation Networks, Armin Mikler, Vasant Honavar, Johnny S. Wong 2017 Iowa State University

Utility-Theoretic Heuristics For Intelligent Adaptive Routing In Large Communcation Networks, Armin Mikler, Vasant Honavar, Johnny S. Wong

Johnny Wong

Utility theory offers an elegant and powerful theoretical framework for design and analysis of autonomous adaptive communication networks. Routing of messages in such networks presents a real-time instance of a multi-criterion quasi-optimization problem in a dynamic and uncertain environment. In this paper, we examine several heuristic decision functions that can be used to guide messages along a near-optimal (e.g., minimum delay) path in a large network. We present an analysis of properties of such heuristics under a set of simplifying assumptions about the network topology and load dynamics. In particular, we identify the conditions under which one such utility-theoretic ...


Vcksm: Verifiable Conjunctive Keyword Search Over Mobile E-Health Cloud In Shared Multi-Owner Settings, Yinbin MIAO, Jianfeng MA, Ximeng LIU 2017 Singapore Management University

Vcksm: Verifiable Conjunctive Keyword Search Over Mobile E-Health Cloud In Shared Multi-Owner Settings, Yinbin Miao, Jianfeng Ma, Ximeng Liu

Research Collection School Of Information Systems

Searchable encryption (SE) is a promising technique which enables cloud users to conductsearch over encrypted cloud data in a privacy-preserving way, especially for the electronichealth record (EHR) system that contains plenty of medical history, diagnosis, radiologyimages, etc. In this paper, we focus on a more practical scenario, also named as theshared multi-owner settings, where each e-health record is co-owned by a fixed numberof parties. Although the existing SE schemes under the unshared multi-owner settingscan be adapted to this shared scenario, these schemes have to build multiple indexes,which definitely incur higher computational overhead. To save bandwidth and computingresources in cloud ...


Community Detection In Social Networks, Ketki Kulkarni 2017 San Jose State University

Community Detection In Social Networks, Ketki Kulkarni

Master's Projects

The rise of the Internet has brought people closer. The number of interactions between people across the globe has gone substantially up due to social awareness, the advancements of the technology, and digital interaction. Social networking sites have built societies, communities virtually. Often these societies are displayed as a network of nodes depicting people and edges depicting relationships, links. This is a good and e cient way to store, model and represent systems which have a complex and rich information. Towards that goal we need to nd e ective, quick methods to analyze social networks. One of the possible solution ...


Influence Detection And Spread Estimation In Social Networks, Madhura Kaple 2017 San Jose State University

Influence Detection And Spread Estimation In Social Networks, Madhura Kaple

Master's Projects

A social network is an online platform, where people communicate and share information with each other. Popular social network features, which make them di erent from traditional communication platforms, are: following a user, re-tweeting a post, liking and commenting on a post etc. Many companies use various social networking platforms extensively as a medium for marketing their products. A xed amount of budget is alloted by the companies to maximize the positive in uence of their product. Every social network consists of a set of users (people) with connections between them. Each user has the potential to extend its in ...


A Neural Network Model For Semi-Supervised Review Aspect Identification, Ying DING, Changlong YU, Jing JIANG 2017 Singapore Management University

A Neural Network Model For Semi-Supervised Review Aspect Identification, Ying Ding, Changlong Yu, Jing Jiang

Research Collection School Of Information Systems

Aspect identification is an important problem in opinion mining. It is usually solved in an unsupervised manner, and topic models have been widely used for the task. In this work, we propose a neural network model to identify aspects from reviews by learning their distributional vectors. A key difference of our neural network model from topic models is that we do not use multinomial word distributions but instead embedding vectors to generate words. Furthermore, to leverage review sentences labeled with aspect words, a sequence labeler based on Recurrent Neural Networks (RNNs) is incorporated into our neural network. The resulting model ...


Comparative Analysis Of Graph Partitioning Algorithms In Context Of Computation Offloading, San Ha Seo, Jeremy Straub 2017 North Dakota State University--Fargo

Comparative Analysis Of Graph Partitioning Algorithms In Context Of Computation Offloading, San Ha Seo, Jeremy Straub

Jeremy Straub

This paper considers the efficacy of using active network technology to offload computation from small mobile devices into network node computing centers. The performance of six algorithms for use in this process is compared and conclusions are drawn.


Socket Golf - Building A Google Cardboard Game In Unity, Caleb P. Carlson 2017 University of Wyoming

Socket Golf - Building A Google Cardboard Game In Unity, Caleb P. Carlson

Honors Theses AY 16/17

Virtual reality is a new and emerging technology in the field of computer science designed to immerse the consumer into the product. To study and learn more about this technology, a four-person team of graduating seniors set out to build a mobile game for Google Cardboard. The game that was created uses the Unity game engine along with Unity multiplayer servers for the development tools. The application was designed to be run using both a Google Cardboard headset and an android controller to allow the user to control the game without removing themselves from the immersive experience.

The idea for ...


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