Cybercrime Deterrence And International Legislation: Evidence From Distributed Denial Of Service Attacks, 2017 Singapore Management University
Cybercrime Deterrence And International Legislation: Evidence From Distributed Denial Of Service Attacks, Kai-Lung Hui, Seung Hyun Kim, Qiu-Hong Wang
Research Collection School Of Information Systems
In this paper, we estimate the impact of enforcing the Convention on Cybercrime (COC) on deterring distributed denial of service (DDOS) attacks. Our data set comprises a sample of real, random spoof-source DDOS attacks recorded in 106 countries in 177 days in the period 2004-2008. We find that enforcing the COC decreases DDOS attacks by at least 11.8 percent, but a similar deterrence effect does not exist if the enforcing countries make a reservation on international cooperation. We also find evidence of network and displacement effects in COC enforcement. Our findings imply attackers in cyberspace are rational, motivated by ...
Vertex Weighted Spectral Clustering, 2017 East Tennessee State University
Vertex Weighted Spectral Clustering, Mohammad Masum
Electronic Theses and Dissertations
Spectral clustering is often used to partition a data set into a specified number of clusters. Both the unweighted and the vertex-weighted approaches use eigenvectors of the Laplacian matrix of a graph. Our focus is on using vertex-weighted methods to refine clustering of observations. An eigenvector corresponding with the second smallest eigenvalue of the Laplacian matrix of a graph is called a Fiedler vector. Coefficients of a Fiedler vector are used to partition vertices of a given graph into two clusters. A vertex of a graph is classified as unassociated if the Fiedler coefficient of the vertex is close to ...
Travel Mode Identification With Smartphone Sensors, 2017 The Graduate Center, City University of New York
Travel Mode Identification With Smartphone Sensors, Xing Su
All Graduate Works by Year: Dissertations, Theses, and Capstone Projects
Personal trips in a modern urban society typically involve multiple travel modes. Recognizing a traveller's transportation mode is not only critical to personal context-awareness in related applications, but also essential to urban traffic operations, transportation planning, and facility design. While the state of the art in travel mode recognition mainly relies on large-scale infrastructure-based fixed sensors or on individuals' GPS devices, the emergence of the smartphone provides a promising alternative with its ever-growing computing, networking, and sensing powers. In this thesis, we propose new algorithms for travel mode identification using smartphone sensors. The prototype system is built upon the ...
Selecting Link Resolver And Knowledge Base Software: Implications Of Interoperability, 2017 James Madison University
Selecting Link Resolver And Knowledge Base Software: Implications Of Interoperability, Cyndy Chisare, Jody C. Fagan, David J. Gaines, Michael Trocchia
Link resolver software and their associated knowledge bases are essential technologies for modern academic libraries. However, because of the increasing number of possible integrations involving link resolver software and knowledge bases, a library’s vendor relationships, product choices, and consortial arrangements may have the most dramatic effects on the user experience and back-end maintenance workloads. A project team at a large comprehensive university recently investigated link resolver products in an attempt to increase efficiency of back-end workflows while maintaining or improving the patron experience. The methodology used for product comparison may be useful for other libraries.
To Look Or Book: An Examination Of Consumers’ Apprehensiveness Toward Internet Use, 2017 Cornell University School of Hotel Administration
To Look Or Book: An Examination Of Consumers’ Apprehensiveness Toward Internet Use, Alex M. Susskind, Mark A. Bonn, Chekitan Dev
Alex M. Susskind
In a series of three studies, a two-factor measure of apprehension toward Internet use was developed and tested among three independent samples of consumers. The relationship between general Internet apprehensiveness (GIA) and transactional Internet apprehensiveness (TIA) was examined in concert with the relationship between consumers’ online information seeking, purchasing intentions, and behaviors. Results indicated that (1) a two-factor measure of GIA and TIA demonstrated construct validity across three independent samples of potential Internet users, (2) GIA is more strongly related to perceptions of Internet use for information seeking compared to online purchasing, and (3) TIA is more strongly related to ...
Neural Net Stock Trend Predictor, 2017 San Jose State University
Neural Net Stock Trend Predictor, Sonal Kabra
This report analyzes new and existing stock market prediction techniques. Traditional technical analysis was combined with various machine-learning approaches such as artificial neural networks, k-nearest neighbors, and decision trees. Experiments we conducted show that technical analysis together with machine learning can be used to profitably direct an investor’s trading decisions. We are measuring the profitability of experiments by calculating the percentage weekly return for each stock entity under study. Our algorithms and simulations are developed using Python. The technical analysis methodology combined with machine learning algorithms show promising results which we discuss in this report.
Predicting Pancreatic Cancer Using Support Vector Machine, 2017 San Jose State University
Predicting Pancreatic Cancer Using Support Vector Machine, Akshay Bodkhe
This report presents an approach to predict pancreatic cancer using Support Vector Machine Classification algorithm. The research objective of this project it to predict pancreatic cancer on just genomic, just clinical and combination of genomic and clinical data. We have used real genomic data having 22,763 samples and 154 features per sample. We have also created Synthetic Clinical data having 400 samples and 7 features per sample in order to predict accuracy of just clinical data. To validate the hypothesis, we have combined synthetic clinical data with subset of features from real genomic data. In our results, we observed ...
Adding Differential Privacy In An Open Board Discussion Board System, 2017 San Jose State University
Adding Differential Privacy In An Open Board Discussion Board System, Pragya Rana
This project implements a privacy system for statistics generated by the Yioop search and discussion board system. Statistical data for such a system consists of various counts, sums, and averages that might be displayed for groups, threads, etc. When statistical data is made publicly available, there is no guarantee of preserving the privacy of an individual. Ideally, any data extracted should not reveal any sensitive information about an individual. In order to help achieve this, we implemented a Differential Privacy mechanism for Yioop. Differential privacy preserves privacy up to some controllable parameters of the number of items or individuals being ...
An Open Source Discussion Group Recommendation System, 2017 San Jose State University
An Open Source Discussion Group Recommendation System, Sarika Padmashali
A recommendation system analyzes user behavior on a website to make suggestions about what a user should do in the future on the website. It basically tries to predict the “rating” or “preference” a user would have for an action. Yioop is an open source search engine, wiki system, and user discussion group system managed by Dr. Christopher Pollett at SJSU. In this project, we have developed a recommendation system for Yioop where users are given suggestions about the threads and groups they could join based on their user history. We have used collaborative filtering techniques to make recommendations and ...
Document Classification Using Machine Learning, 2017 San Jose State University
Document Classification Using Machine Learning, Ankit Basarkar
To perform document classification algorithmically, documents need to be represented such that it is understandable to the machine learning classifier. The report discusses the different types of feature vectors through which document can be represented and later classified. The project aims at comparing the Binary, Count and TfIdf feature vectors and their impact on document classification. To test how well each of the three mentioned feature vectors perform, we used the 20-newsgroup dataset and converted the documents to all the three feature vectors. For each feature vector representation, we trained the Naïve Bayes classifier and then tested the generated ...
Credit Scoring Using Logistic Regression, 2017 San Jose State University
Credit Scoring Using Logistic Regression, Ansen Mathew
This report presents an approach to predict the credit scores of customers using the Logistic Regression machine learning algorithm. The research objective of this project is to perform a comparative study between feature selection and feature extraction, against the same dataset using the Logistic Regression machine learning algorithm. For feature selection, we have used Stepwise Logistic Regression. For feature extraction, we have used Singular Value Decomposition (SVD) and Weighted Singular Value Decomposition (SVD). In order to test the accuracy obtained using feature selection and feature extraction, we used a public credit dataset having 11 features and 150,000 records. After ...
Web - Based Office Market, 2017 San Jose State University
Web - Based Office Market, Manodivya Kathiravan
People who work in an office often have different pools of resources that they want to exchange. They want to trade their resources/work(seller) with a person who wants that particular resource(buyer) and in return get another resource the buyer offers. These kind of exchanges are often called Barter-exchanges where an item is traded for another item without the involvement of actual money. An exchange is set to be complete when there is a match between an available item and a desired item. This exchange is called direct exchange. When an item desired by one user is made ...
Community Detection In Social Networks, 2017 San Jose State University
Community Detection In Social Networks, Ketki Kulkarni
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 ...
A Period Examination Through Contemporary Energy Analysis Of Kevin Roche’S Fine Arts Center At University Of Massachusetts-Amherst, 2017 University of Massachusetts - Amherst
A Period Examination Through Contemporary Energy Analysis Of Kevin Roche’S Fine Arts Center At University Of Massachusetts-Amherst, L Carl Fiocchi Jr
L. Carl Fiocchi
Studies of buildings belonging to a subset of Modernist architecture, Brutalism, have included discussions pertaining to social and architectural history, critical reception, tectonic form and geometry inspirations, material property selections, period technology limitations, and migration of public perceptions. Evaluations of Brutalist buildings’ energy related performances have been restricted to anecdotal observations with particular focus on the building type’s poor thermal performance, a result of the preferred construction method, i.e. monolithic reinforced concrete used as structure, interior finish and exterior finish. A valid criticism, but one that served to dismiss discussion that the possibility of other positive design strategies ...
Evolvability: What Is It And How Do We Get It?, 2017 University of Puget Sound
Evolvability: What Is It And How Do We Get It?, Matthew Moreno
Honors Program Theses
Biological organisms exhibit spectacular adaptation to their environments. However, another marvel of biology lurks behind the adaptive traits that organisms exhibit over the course of their lifespans: it is hypothesized that biological organisms also exhibit adaptation to the evolutionary process itself. That is, biological organisms are thought to possess traits that facilitate evolution. The term evolvability was coined to describe this type of adaptation. The question of evolvability has special practical relevance to computer science researchers engaged in longstanding efforts to harness evolution as an algorithm for automated design. It is hoped that a more nuanced understanding of biological evolution ...
Transcriptase–Light: A Polymorphic Virus Construction Kit, 2017 San Jose State University
Transcriptase–Light: A Polymorphic Virus Construction Kit, Saurabh Borwankar
This project creates Transcriptase–Light, a new polymorphic construction kit. We perform an experiment with the Transcriptase–Light against a hidden Markov ...
Reducing Query Latency For Information Retrieval, 2017 San Jose State University
Reducing Query Latency For Information Retrieval, Swapnil Satish Kamble
As the world is moving towards Big Data, NoSQL (Not only SQL) databases are gaining much more popularity. Among the other advantages of NoSQL databases, one of their key advantage is that they facilitate faster retrieval for huge volumes of data, as compared to traditional relational databases. This project deals with one such popular NoSQL database, Apache HBase. It performs quite efficiently in cases of retrieving information using the rowkey (similar to a primary key in a SQL database). But, in cases where one needs to get information based on non-rowkey columns, the response latency is higher than what we ...
Switching Between Page Replacement Algorithms Based On Work Load During Runtime In Linux Kernel, 2017 San Jose State University
Switching Between Page Replacement Algorithms Based On Work Load During Runtime In Linux Kernel, Praveen Subramaniyam
Today’s computers are equipped with multiple processor cores to execute multiple programs effectively at a single point of time. This increase in the number of cores needs to be equipped with a huge amount of physical memory to keep multiple applications in memory at a time and to effectively switch between them, without getting affected by the low speed disk memory. The physical memory of today’s world has become so cheap such that all the computer systems are always equipped with sufficient amount of physical memory required effectively to run most of the applications. Along with the memory ...
Shopbot: An Image Based Search Application For E-Commerce Domain, 2017 San Jose State University
Shopbot: An Image Based Search Application For E-Commerce Domain, Nishant Goel
For the past few years, e-commerce has changed the way people buy and sell products. People use this business model to do business over the Internet. In this domain, Human-Computer Interaction has been gaining momentum. Lately, there has been an upsurge in agent based applications in the form of intelligent personal assistants (also known as Chatbots) which make it easier for users to interact with digital services via a conversation, in the same way we talk to humans. In e- commerce, these assistants offer mainly text-based or speech based search capabilities. They can handle search for most products, but cannot ...
Cascaded Facial Detection Algorithms To Improve Recognition, 2017 San Jose State University
Cascaded Facial Detection Algorithms To Improve Recognition, Edmund Yee
The desire to be able to use computer programs to recognize certain biometric qualities of people have been desired by several different types of organizations. One of these qualities worked on and has achieved moderate success is facial detection and recognition. Being able to use computers to determine where and who a face is has generated several different algorithms to solve this problem with different benefits and drawbacks. At the backbone of each algorithm is the desire for it to be quick and accurate. By cascading face detection algorithms, accuracy can be improved but runtime will subsequently be increased. Neural ...