5153 research outputs found
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Risk Parity Optimality
No full textA poster summarizing some of the results of research by Gregg S. Fisher, Philip Z. Maymin, Zakhar G. Maymin that was published in Journal of Portfolio Management (2015), 41:2, 42-56 under the title "Risk Parity Optimality"
2016 Presidential Election Prediction using Twitter
No full textNowadays, data of social media websites are getting more and more popular to be used as one of the most important data source for the data mining from which we can find the useful and interesting patterns. In this project, base on twitter data set that I collect using twitter API, I performed the sentimental mining and topic modeling. In the data collection phase, I used keywords such as the candidates’ name to filter the related data decreasing the noise to the most extend. To accomplish the sentimental mining, I chose Naïve Bayes algorithm and Support vector machine Model(SVM) two of the most commonly used algorithms that can be used as the classifier in the sentimental analysis. Then I trained these classifiers using a data set which was also from twitter and was related to 2016 presidential election from Kaggle and made the predication using twitter data set that I collected. Besides, Latent Dirichlet Allocation model was used to fulfill the topic modeling analysis finding the most frequent topics from the data of presidential election related tweets. At last, I evaluated the performance of each classification algorithm
ISIS: The Past, Present, and Future of the Islamic State
No full textThe so-called Islamic State (IS) has shocked the world with its intense brutality, the extent of its territorial and psychological control, and the speed with which it rose to power. I will approach the questions of what factors allowed and caused this group to come into power and to stay as strong as it has, and what might be expected for its future. I will provide summaries of historical contexts within Iraq and Syria, the current economic and political situation in the Islamic State, and an analysis of its strengths and weaknesses based on internal and external factors, showing that although the battle with the Islamic State is not finished, the Caliphate ultimately cannot endure
An Automated Adaptive Mobile Learning System Using Optimal Shortest Path Algorithms
No full textTechnological innovation opens the door to create a personal learning experience for any student. In this research, we discuss adaptive learning techniques and the style of learning that integrates existing learning techniques combined with new ideas. To create an effective user friendly learning environment, adaptive learning techniques should be used in order to identify the personal needs of students and reduce their individual knowledge gaps. The result will produce learning path containing relevant content that will provide a better learning direction for each student. This dissertation explores the opportunity of using adaptive learning techniques to identify the personal needs of each student by combining different learning styles, student profiles and individualized course content. By using a directed graph, we are able to represent an accurate picture of the course descriptions for online courses through computer-based implementation of various educational systems. E-learning (electronic learning) and m-learning (mobile learning) systems are modeled as a weighted directed graph where each node represents a course unit. The Learning Path Graph represents and describes the structure of the domain knowledge, including the learning goals, and all other available learning paths. In this research, we propose a system prototype that implements optimal adaptive learning path algorithms using students’ information from their profiles and their learning style. Our goal is to improve students’ learning performances through the m-learning system in order to provide suitable course contents sequenced in a dynamic form for each student
From the Inspiration to the Dedication: The Journey to Academic Book Authorship
No full textCarrie A. Picardi's poster on book authorship and publishing
A Grounded Theory of Persistence in a Limited-Residency Doctoral Program
No full textApproximately 50% of doctoral students in social science, humanities, and educational doctoral programs fail to earn their Ph.D. This number is 10% to 15% higher for students enrolled in online or limited-residency programs. Using in-depth interviews and qualitative data analysis techniques, this grounded-theory study examined participants’ recollections of their experience as students in a limited-residency doctoral program and their reasons for withdrawal while working on their dissertation. The resultant theory clarified relationships between attrition and support issues (i.e., advisor support, dissertation process support and program office support). The theoretical model helps identify steps faculty and administration may take in order to reduce high levels of attrition
Analyzing Household Participation in the Single-Stream Recycling System
No full textAs an effort to increase recycling in the United States, local Governments adopted the single-stream recycling system, in which different recycling materials are mixed during its initial collection. Although this resulted in an increase in the volume of recyclables deposited by individuals, it has also exponentially increased the contamination of recyclables. This affects the value of recyclables when they are sold to recycling companies. This research aim to analyze household participation and its effect on the singles-stream recycling system
A Multi-Layer Approach For Detection Of Selective Forwarding Attacks In Wireless Sensor Networks
No full textWireless sensor networks (WSNs) are increasingly used due to their broad range of important applications in both military and civilian domains. Security is a major threat in WSNs. WSNs are prone to several types of security attacks. Sensor nodes have limited capacities and are deployed in dangerous locations; therefore, they are vulnerable to different types of attacks, including wormhole, sinkhole, and selective forwarding attacks. Security attacks are classified as data traffic and routing attacks. These security attacks could affect the most significant applications of WSNs, namely, military surveillance, traffic monitoring, and healthcare. Therefore, many approaches were suggested in literature to detect security attacks on the network layer in WSNs. The network layer is of paramount significance to the security of WSNs to prevent exploitation of their confidentiality, privacy, availability, integrity, and authenticity. Reliability, energy efficiency, and scalability are strong constraints on sensor nodes that affect the security of WSNs. Because sensor nodes have limited capabilities in most of these areas, selective forwarding attacks cannot be easily detected in networks. In this dissertation, an approach to selective forwarding detection (SFD) is suggested. The approach has three layers: MAC pool IDs, rule-based processing, and anomaly detection. It maintains the safety of data transmission between a source node and base station while detecting selective forwarding attacks. Furthermore, the approach is reliable, energy efficient, and scalable
A Majority Voting Technique for Wireless Intrusion Detection Systems
No full textThis poster aims to build a misuse Wireless Local Area Network Intrusion Detection System (WIDS), and to discover some important fields in WLAN MAC-layer frame to differentiate the attackers from the legitimate devices. We tested several machine-learning algorithms, and found some promising ones to improve the accuracy and computation time on a public dataset. The Bagging classifier and our customized voting technique have good results (about 96.25% and 96.32% respectively) when tested on all the features
Root Herbivory has More Influence on Arabidopsis thaliana Survival Rates than Leaf Herbivory
No full textHypothesis: We hypothesize that the hypocotyl length, leaves number and survival rate will be greater in plants with cut leaves than cut roots. Background: Plants rely on root absorption and leaf photosynthesis to grow. Roots not only absorb nutrition from soil but also function in nutrient storage and reproduction. We exposed Arabidopsis thaliana to three different treatments: cutting leaves, cutting roots and a control group. We observed their growth, morphology and the survival rate