Table Of Contents Jitim Vol 28 Issue 2, 2019,
2019
California State University, San Bernardino
Table Of Contents Jitim Vol 28 Issue 2, 2019
Journal of International Technology and Information Management
Table of Contents JITIM 2, 2019
A Longitudinal Analysis Of The Impact Of The Indicators In The Networked Readiness Index (Nri),
2019
The University of Scranton
A Longitudinal Analysis Of The Impact Of The Indicators In The Networked Readiness Index (Nri), Satya Pratipatti, Ahmed Gomaa
Journal of International Technology and Information Management
World Economic Forum publishes the Networked Readiness Index (NRI) annually, to reflect the Information and Communication Technology (ICT) status of different countries. The NRI is developed by aggregating 53 indicators. The study identifies the most critical indicators to focus on, to improve the NRI status of countries at different stages of economic development. It uses data from 117 countries and analyzes the changes in the indicators along with their impacts between the years 2012 and 2016. The study explores the differences between countries by grouping them into four groups based on their NRI status. The analysis identifies six indicators with …
The Impact Of Changes Mislabeled By Szz On Just-In-Time Defect Prediction,
2019
Singapore Management University
The Impact Of Changes Mislabeled By Szz On Just-In-Time Defect Prediction, Yuanrui Fan, Xin Xia, Daniel A. Costa, David Lo, Ahmed E. Hassan, Shanping Li
Research Collection School Of Computing and Information Systems
Just-in-Time (JIT) defect prediction—a technique which aims to predict bugs at change level—has been paid more attention. JIT defect prediction leverages the SZZ approach to identify bug-introducing changes. Recently, researchers found that the performance of SZZ (including its variants) is impacted by a large amount of noise. SZZ may considerably mislabel changes that are used to train a JIT defect prediction model, and thus impact the prediction accuracy. In this paper, we investigate the impact of the mislabeled changes by different SZZ variants on the performance and interpretation of JIT defect prediction models. We analyze four SZZ variants (i.e., B-SZZ, …
Survival Theory Modelling For Information Diffusion,
2019
Florida Institute of Technology
Survival Theory Modelling For Information Diffusion, Akshay Aravamudan
Theses and Dissertations
Information diffusion is the spread of information within a network. In this thesis, we model information diffusion as a survival process. We have adopted an existing algorithm called NetRate for modelling information diffusion. This model involves finding the distribution of trasmission time between two nodes in the network. We modify NetRate’s concave-down log-likelihood expression by adding partial parentage information and formulate an Expectation-Minimization (EM) algorithm to learn the parameters. We also describe a simulation scheme for NetRate inspired by point process simulation strategies. Using the assumptions of the NetRate model, we derive a a method to model popularity as a …
High Dimensional Data Clustering Using Self-Organized Map,
2019
Universitas Brawijaya, Indonesia
High Dimensional Data Clustering Using Self-Organized Map, Ruth Ema Febrita, Wayan Firdaus Mahmudy, Aji Prasetya Wibawa
Knowledge Engineering and Data Science
As the population grows and e economic development, houses could be one of basic needs of every family. Therefore, housing investment has promising value in the future. This research implements the Self-Organized Map (SOM) algorithm to cluster house data for providing several house groups based on the various features. K-means is used as the baseline of the proposed approach. SOM has higher silhouette coefficient (0.4367) compared to its comparison (0.236). Thus, this method outperforms k-means in terms of visualizing high-dimensional data cluster. It is also better in the cluster formation and regulating the data distribution.
Adam Optimization Algorithmfor Wide And Deep Neural Network,
2019
International Islamic University Malaysia
Adam Optimization Algorithmfor Wide And Deep Neural Network, Imran Khan Mohd Jais, Amelia Ritahani Ismail
Knowledge Engineering and Data Science
The objective of this research is to evaluate the effects of Adam when used together with a wide and deep neural network. The dataset used was a diagnostic breast cancer dataset taken from UCI Machine Learning. Then, the dataset was fed into a conventional neural network for a benchmark test. Afterwards, the dataset was fed into the wide and deep neural network with and without Adam. It was found that there were improvements in the result of the wide and deep network with Adam. In conclusion, Adam is able to improve the performance of a wide and deep neural network.
Crude Palm Oil Prediction Based On Back Propagation Neutral Network Approach,
2019
Mulawarman University, Indonesia
Crude Palm Oil Prediction Based On Back Propagation Neutral Network Approach, Hijratul Aini, Haviluddin Haviluddin
Knowledge Engineering and Data Science
Crude palm oil (CPO) production at PT. Perkebunan Nusantara (PTPN) XIII from January 2015 to January 2018 have been treated. This paper aims to predict CPO production using intelligent algorithms called Backpropagation Neural Network (BPNN). The accuracy of prediction algorithms have been measured by mean square error (MSE). The experiment showed that the best hidden layer architecture (HLA) is 5-10-11-12-13-1 with learning function (LF) of trainlm, activation function (AF) of logsig and purelin, and learning rate (LR) of 0.5. This architecture has a good accuracy with MSE of 0.0643. The results showed that this model can predict CPO production in …
The Diffusion Of Ict For Corruption Detectionin Open Government Data,
2019
University Teknologi Mara, Malaysia
The Diffusion Of Ict For Corruption Detectionin Open Government Data, Darusalam Darusalam, Jamaliah Said, Normah Omar, Marijn Janssen, Kazi Sohag
Knowledge Engineering and Data Science
Corruption occurs in many places within the government. To tackle the issue, open data can be used as one of the tools in creating more insight into the government. The premise of this paper is to support the notion that data opening can bring up new ways of fighting corruption. The current paper aimed at investigating how open data can be employed to detect corruption. This open data is trivial due to challenges like information asymmetry among stakeholders, data might only be opened partly, different sources of data need to be combined, and data might not be easy to use, …
Selection Of Marine Security Policyusing Fuzzy-Ahp Topsis Hybrid Approach,
2019
Islamic University of Madura, Indonesia
Selection Of Marine Security Policyusing Fuzzy-Ahp Topsis Hybrid Approach, Hozairi Hozairi, Buhari Buhari, Heru Lumaksono, Marcus Tukan
Knowledge Engineering and Data Science
The research was focused on the integration of Fuzzy set theory with Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to choose the optimum maritime security policy to achieve Indonesia recognition as the world's maritime axis. The method used is AHP with fuzzy based enhancement. Here, the weight of each criterion is calculated to overcome the criticism of the scale of unbalanced rating, uncertainty, and inaccuracy in the pairwise of comparison process. The best recommendation for Indonesian maritime policies is multi task single agency which is greatly infuenced by several factors such as …
Nonlinear Observer For Visual-Inertial Navigation Using Intermittent Landmark Measurements,
2019
Western University
Nonlinear Observer For Visual-Inertial Navigation Using Intermittent Landmark Measurements, Miaomiao Wang
Western Research Forum
The development of reliable orientation, position and linear velocity estimation algorithms for the 3D visual-inertial navigation system (VINS) is instrumental in many applications, such as autonomous underwater vehicles (AUVs), and unmanned aerial vehicles (UAVs). It is extremely important when the global position system (GPS) is not available in GPS-denied environments. Recently, observers design for VINS using landmark position measurements from Kinect sensors or stereo cameras has been increasingly investigated in the literature.
The aim of this work is to design a nonlinear observer for VINS under the assumption that landmark position measurements are intermittent. In practice, the landmark measurements are …
A Resource Constrained Shortest Paths Approach To Reducing Personal Pollution Exposure,
2019
Portland State University
A Resource Constrained Shortest Paths Approach To Reducing Personal Pollution Exposure, Elling Payne
REU Final Reports
As wildfires surge in frequency and impact in the Pacific Northwest, in tandem with increasingly traffic-choked roads, personal exposure to harmful airborne pollutants is a rising concern. Particularly at risk are school-age children, especially those living in disadvantaged communities near major motorways and industrial centers. Many of these children must walk to school, and the choice of route can effect exposure. Route-planning applications and frameworks utilizing computational shortest paths methods have been proposed which consider personal exposure with reasonable success, but few have focused on pollution exposure, and all have been limited in scalability or geographic scope. This paper addresses …
Large-Scale Data Analysis And Deep Learning Using Distributed Cyberinfrastructures And High Performance Computing,
2019
Louisiana State University and Agricultural and Mechanical College
Large-Scale Data Analysis And Deep Learning Using Distributed Cyberinfrastructures And High Performance Computing, Richard Dodge Platania
LSU Doctoral Dissertations
Data in many research fields continues to grow in both size and complexity. For instance, recent technological advances have caused an increased throughput in data in various biological-related endeavors, such as DNA sequencing, molecular simulations, and medical imaging. In addition, the variance in the types of data (textual, signal, image, etc.) adds an additional complexity in analyzing the data. As such, there is a need for uniquely developed applications that cater towards the type of data. Several considerations must be made when attempting to create a tool for a particular dataset. First, we must consider the type of algorithm required …
Influence Spread In Two-Layer Interdependent Networks: Designed Single-Layer Or Random Two-Layer Initial Spreaders?,
2019
University of Kentucky
Influence Spread In Two-Layer Interdependent Networks: Designed Single-Layer Or Random Two-Layer Initial Spreaders?, Hana Khamfroush, Nathaniel Hudson, Samuel Iloo, Mahshid R. Naeini
Computer Science Faculty Publications
Influence spread in multi-layer interdependent networks (M-IDN) has been studied in the last few years; however, prior works mostly focused on the spread that is initiated in a single layer of an M-IDN. In real world scenarios, influence spread can happen concurrently among many or all components making up the topology of an M-IDN. This paper investigates the effectiveness of different influence spread strategies in M-IDNs by providing a comprehensive analysis of the time evolution of influence propagation given different initial spreader strategies. For this study we consider a two-layer interdependent network and a general probabilistic threshold influence spread model …
Sparse General Non-Negative Matrix Factorization Based On Left Semi-Tensor Product,
2019
Santa Clara University
Sparse General Non-Negative Matrix Factorization Based On Left Semi-Tensor Product, Zigang Chen, Lixiang Li, Haipeng Peng, Yuhong Liu, Haihua Zhu, Yixian Yang
Computer Science and Engineering
The dimension reduction of large scale high-dimensional data is a challenging task, especially the dimension reduction of face data and the accuracy increment of face recognition in the large scale face recognition system, which may cause large storage space and long recognition time. In order to further reduce the recognition time and the storage space in the large scale face recognition systems, on the basis of the general non-negative matrix factorization based on left semi-tensor (GNMFL) without dimension matching constraints proposed in our previous work, we propose a sparse GNMFL/L (SGNMFL/L) to decompose a large number of face data sets …
Authentication And Sql-Injection Prevention Techniques In Web Applications,
2019
University of South Florida
Authentication And Sql-Injection Prevention Techniques In Web Applications, Cagri Cetin
USF Tampa Graduate Theses and Dissertations
This dissertation addresses the top two “most critical web-application security risks” by combining two high-level contributions.
The first high-level contribution introduces and evaluates collaborative authentication, or coauthentication, a single-factor technique in which multiple registered devices work together to authenticate a user. Coauthentication provides security benefits similar to those of multi-factor techniques, such as mitigating theft of any one authentication secret, without some of the inconveniences of multi-factor techniques, such as having to enter passwords or biometrics. Coauthentication provides additional security benefits, including: preventing phishing, replay, and man-in-the-middle attacks; basing authentications on high-entropy secrets that can be generated and updated automatically; …
Trippit: An Optimal Itinerary Generator,
2019
Santa Clara University
Trippit: An Optimal Itinerary Generator, Andrew Nguyen, Osama Shoubber
Computer Science and Engineering Senior Theses
Travelers often lose interest and joy when traveling in tourist-packed areas around the world. As more restaurants and attractions open up in popular cities, the wait and travel time from one location to another inevitably increases. Each attraction has certain hours throughout the day where visitors surge and the wait times increase. In addition, traffic and travel time is an important factor to consider when looking to optimize ones trip. However, with large amounts of attractions, it is difficult to calculate and consider the most optimal routes and times an individual should use to visit each possible attraction. Travelers ultimately …
Homebook,
2019
Santa Clara University
Homebook, Stephen Poth, Simon Stauber, Jake Vargas
Computer Science and Engineering Senior Theses
Having a reliable address system is something that is often taken for granted, but simply having one comes with immense benefits. People can easily find locations of friends and family, services like taxis know exactly where to pick customers up, and emergency response units can accurately find the scene of emergencies quickly. However, in many developing countries, these are luxuries only afforded by the wealthy and privileged neighborhoods. Locations are given haphazardly through description, often leading to late arrivals. In some cases this can be a dire possibility. Our solution aims to change this by developing a mobile application that …
Deaddropbox: A Time-Locked Safe For Data,
2019
Santa Clara University
Deaddropbox: A Time-Locked Safe For Data, Robert Herriott, Peter Paulson, Nathaniel Kragas
Computer Science and Engineering Senior Theses
This project is a proof-of-concept for software which would allow users to securely store sensitive data in such a way that it is difficult or impossible for third parties to compromise the data, even when the user is compelled to assist them. It will operate by storing data across multiple devices in a unreadable form so that it is inaccessible until the data is reunified. The user may specify the circumstances under which different pieces of the data may be accessed, so that it is impossible to access under circumstances of duress.
A Questioning Agent For Literary Discussion,
2019
Santa Clara University
A Questioning Agent For Literary Discussion, Robbie Culkin, Tim Shur
Computer Science and Engineering Senior Theses
Developing a compelling and cohesive thesis for analytical writing can be a daunting task, even for those who have produced many written works, and finding others to engage with in literary discussion can be equally challenging. In this paper, we describe our solution: Questioner, a discussion tool that engages users in conversation about an academic topic of their choosing for the purpose of collecting thoughts on a subject and constructing an argument. This system will ask informed questions that prompt further discussion about the topic and provide a discussion report after the conversation has ended. We found that our system …
Doorbell For The Hearing Impaired,
2019
Santa Clara University
Doorbell For The Hearing Impaired, Shannen Edwin, Dominic Magdaluyo
Computer Science and Engineering Senior Theses
Doorbell options for hearing impaired individuals is seriously limited. Affordable solutions are not scalable while other solutions are expensive. With this in mind, we designed a scalable and affordable system that will be beneficial to hearing impaired individuals in a small aspect of their life. Our solution takes advantage of affordable IoT devices and software to build a proof of concept. Due to the scope of the project, we only designed a proof of concept, in the hope that a company can design a viable product that will not only benefit hearing impaired individuals but bring a powerful IoT system …
