Databases and Information Systems Commons^™

Data Mining The Functional Characterizations Of Proteins To Predict Their Cancer-Relatedness, Peter Revesz, Christopher Assi

School of Computing: Faculty Publications

This paper considers two types of protein data. First, data about protein function described in a number of ways, such as, GO terms and PFAM families. Second, data about whether individual proteins are experimentally associated with cancer by an anomalous elevation or lowering of their expressions within cancerous cells. We combine these two types of protein data and test whether the first type of data, that is, the functional descriptors, can predict the second type of data, that is, cancer-relatedness. By using data mining and machine learning, we derive a classifier algorithm that using only GO term and PFAM family …

Guest Editorial: Selected Papers From Icimcs 2011, Chong-Wah Ngo, Changsheng Xu, Xiao Wu, Abdulmotaleb El Saddik

Research Collection School Of Computing and Information Systems

International Conference on Internet Multimedia Computing and Services (ICIMCS) is an annual conference sponsored by ACM SIGMM China Chapter. The conference is especially interested in the latest technologies and applications that deal with the web-scale processing and management of heterogeneous data from the Internet for multimedia computing and service. ICIMCS 2011 held in Chengdu, China— the ancient hometown of lovely panda. The conference has attracted around 80 participants, including researchers from academia and industries across ten countries/regions, for sharing their recent works in the topics ranging from visual information analysis and mining, query processing and search, multimedia privacy and security.

Synthetic Controllable Turbulence Using Robust Second Vorticity Confinement, Shengfeng He, Rynson W. H. Lau

Research Collection School Of Computing and Information Systems

Capturing fine details of turbulence on a coarse grid is one of the main tasks in real-time fluid simulation. Existing methods for doing this have various limitations. In this paper, we propose a new turbulence method that uses a refined second vorticity confinement method, referred to as robust second vorticity confinement, and a synthesis scheme to create highly turbulent effects from coarse grid. The new technique is sufficiently stable to efficiently produce highly turbulent flows, while allowing intuitive control of vortical structures. Second vorticity confinement captures and defines the vortical features of turbulence on a coarse grid. However, due to …

Online Multi-Modal Distance Learning For Scalable Multimedia Retrieval, Hao Xia, Pengcheng Wu, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

In many real-word scenarios, e.g., multimedia applications, data often originates from multiple heterogeneous sources or are represented by diverse types of representation, which is often referred to as "multi-modal data". The definition of distance between any two objects/items on multi-modal data is a key challenge encountered by many real-world applications, including multimedia retrieval. In this paper, we present a novel online learning framework for learning distance functions on multi-modal data through the combination of multiple kernels. In order to attack large-scale multimedia applications, we propose Online Multi-modal Distance Learning (OMDL) algorithms, which are significantly more efficient and scalable than the …

Online Multiple Kernel Classification, Steven C. H. Hoi, Rong Jin, Peilin Zhao, Tianbao Yang

Research Collection School Of Computing and Information Systems

Although both online learning and kernel learning have been studied extensively in machine learning, there is limited effort in addressing the intersecting research problems of these two important topics. As an attempt to fill the gap, we address a new research problem, termed Online Multiple Kernel Classification (OMKC), which learns a kernel-based prediction function by selecting a subset of predefined kernel functions in an online learning fashion. OMKC is in general more challenging than typical online learning because both the kernel classifiers and the subset of selected kernels are unknown, and more importantly the solutions to the kernel classifiers and …

K-Pop Live: Social Networking & Language Learning Platform, Thomas Chua, Chin Leng Ong, Kian Ming Png, Aloysius Lau, Houston Toh, Feida Zhu, Kyong Jin Shim, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

K-Pop live is a social networking and language learning platform developed by an undergraduate student team from Singapore Management University. K-Pop live aims to combine social media together with gamification to promote Korean culture. It consolidates all relevant Tweets from Twitter as well as videos from YouTube. The platform allows the user to connect with his friends who share similar interests in terms of K-pop artists and music.

What Kind Of #Conversation Is Twitter? Mining #Psycholinguistic Cues For Emergency Coordination, Hemant Purohit, Andrew Hampton, Valerie L. Shalin, Amit P. Sheth, John M. Flach, Shreyansh Bhatt

Kno.e.sis Publications

The information overload created by social media messages in emergency situations challenges response organizations to find targeted content and users. We aim to select useful messages by detecting the presence of conversation as an indicator of coordinated citizen action. Using simple linguistic indicators associated with conversation analysis in social science, we model the presence of conversation in the communication landscape of Twitter in a large corpus of 1.5M tweets for various disaster and non-disaster events spanning different periods, lengths of time and varied social significance. Within Replies, Retweets and tweets that mention other Twitter users, we found that domain-independent, linguistic …

Stock Market Prediction Without Sentiment Analysis: Using A Web-Traffic Based Classifier And User-Level Analysis, Pierpaolo Dondio

Conference papers

This paper provides further evidence on the predictive power of online community traffic with regard to stock prices. Using the largest dataset to date, spanning 8 years and almost the complete set of SP500 stocks, we train a classifier using a set of features entirely extracted from web-traffic data of financial online communities. The classifier is shown to outperform the predictive power of a baseline classifier solely based on price time-series, and to have similar performances as the classifier built considering price and traffic features together. The best predictive performances are achieved when information about stock capitalization is coupled with …

Detecting Mobility Patterns In Mobile Phone Data From The Ivory Coast, Matthew Dixon, Spencer P. Aiello, Funmi Fapohunda, William Goldstein

Business Analytics and Information Systems

This paper investigates the Data for Development (D4D) challenge [3], an open challenge set by the French mobile phone company, Orange, who have provided anonymized records of their customers in the Ivory Coast. This data spans a 5 month (150 day) horizon spread across 4 different sets containing antenna-to-antenna traffic, trace data for 50,000 customers at varying spatial resolution, and social graphs for 5,000 customers. By leveraging cloud-based and open-source analytics infrastructure to (1) merge the D4D datasets with Geographic Information System (GIS) data and (2) apply data mining algorithms, this paper presents a number of techniques for detecting mobility …

Multiple Bounding Boxes Algorithm In Collision Detection And Its Performances In Sequential Vs Cuda Parallel Processing, Min Qi

Electronic Theses and Dissertations

The traditional method for detecting collisions in a 2D computer game uses a axisaligned bounding box around each sprite, and checks to determine if the bounding boxes overlap periodically. Using this single bounding box method may result in a large amount of pixel intersection tests, since a sprite may be composed of areas where the pixels are empty and the intersecting bounding box test results in false positives.

Our algorithm analysis shows that the optimal two or three bounding boxes is the best partition we can get for a reasonable time complexity. The results further show significantly diminishing returns for …

California State University, San Bernardino Managing Cloud Computing Resources With Cloudstack Using Kvm Hypervisor, Ian Buckner Jacobs

Theses Digitization Project

The purpose of this project is to present a detailed description of the Enterprise Cloud Computing implementation of CloudStack using KVM. It will explain the purpose and features of the system, the interfaces of the system, what the system will do, and the constraints or limitations implementing CloudStack with the hardware available for this study.

Online Examination System, Yuvesh Kumar Singh

Theses Digitization Project

The purpose of this project focused on how to implement a secure environment for online-examination in an academic and business environment without the need of any special network topologies and hardware devices. It will not only reduce the instructor's load, but will also enhance the system flexibility to fit every instructor's needs and from the examinees point of view. Contains source code.

Gradebadge: Development Of A Cloud-Based Reward Application, Erwin Toni Soekianto

Theses Digitization Project

The purpose of this project is to investigate the use of cloud-based services to deliver cutting edge applications. For this purpose, a prototype of a reward application using badges, called Gradebadge, was developed to illustrate and explore this emerging paradigm.

Ticketing And Event Management Web Service, Nikolay Figurin

Theses Digitization Project

The purpose of this project was creating a web based application that included: user account creation, event creation per user, tiered ticket sales per event, search capabilities, a focus on scalability and data redundancy, a focus on verification of event creator identities and administration features, a focus on account expandability, an ability to easily expand functionality, ease of migration and stability, low and inexpensive maintenance, as well as an optimal framework relying on a platform as a service content delivery network with the option of database abstraction.

Online Graduate Application System, You Li

Theses Digitization Project

The purpose of Online Graduate Application System (OGAS) is to allow potential Computer Science and Engineering graduate students to submit and track their online applications. In addition, applicants can change and modify their references via OGAS. As part of the application requirements, the system will allow recommenders to submit and /or upload their recommendations online.

A Hybrid Approach To Finding Relevant Social Media Content For Complex Domain Specific Information Needs, Delroy H. Cameron, Amit P. Sheth, Nishita Jaykumar, Gaurish Anand, Krishnaprasad Thirunarayan, Gary Alan Smith

Kno.e.sis Publications

While contemporary semantic search systems offer to improve classical keyword-based search, they are not always adequate for complex, domain specific information needs. Some complex search situations require knowledge of both ontological concepts as well as 'intelligible constructs' not typically modeled in ontologies. Intelligible constructs convey essential information, which may be important to the holistic information needs of information seekers. Such constructs may include notions of intensity, frequency, interval, dosage, emotion, sentiment, equivalence, synonymy, negation, parts-of-speech, etc. However, few search systems utilize both structured background knowledge (ontologies) and the aforementioned knowledge for query interpretation in domain specific searches. Instead, there is …

Traffic Analytics Using Probabilistic Graphical Models Enhanced With Knowledge Bases, Pramod Anantharam, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

Graphical models have been successfully used to deal with uncertainty, incompleteness, and dynamism within many domains. These models built from data often ignore preexisting declarative knowledge about the domain in the form of ontologies and Linked Open Data (LOD) that is increasingly available on the web. In this paper, we present an approach to leverage such 'top-down' domain knowledge to enhance 'bottom-up' building of graphical models. Specifically, we propose three operations on the graphical model structure to enrich it with nodes, edges, and edge directions. We illustrate the enrichment process using traffic data from 511.org and declarative knowledge from ConceptNet. …

Advancing Data Reuse In Phyloinformatics Using An Ontology-Driven Semantic Web Approach, Maryam Panahiazar, Amit P. Sheth, Ajith Harshana Ranabahu, Rutger Vos, Jim Leebens-Mack

Kno.e.sis Publications

Phylogenetic analyses can resolve historical relationships among genes, organisms or higher taxa. Understanding such relationships can elucidate a wide range of biological phenomena, including, for example, the importance of gene and genome duplications in the evolution of gene function, the role of adaptation as a driver of diversification, or the evolutionary consequences of biogeographic shifts. Phyloinformaticists are developing data standards, databases and communication protocols (e.g. Application Programming Interfaces, APIs) to extend the accessibility of gene trees, species trees, and the metadata necessary to interpret these trees, thus enabling researchers across the life sciences to reuse phylogenetic knowledge. Specifically, Semantic Web …

Dependence On Cyberscribes - Issues In E-Security, Thomas R. Mclean, Alexander B. Mclean

Journal of Business & Technology Law

No abstract provided.

Gradeboard: A Cloud-Based Solution For A Student Grading System, Manoj Kulkarni

Theses Digitization Project

The purpose of the GradeBoard application is to develop a mobile application as a front end to interact with data stored in a cloud-based system. It leverages cloud computing features such as auto-scaling, load-balancing and NoSQL data stores. The GradeBoard application helps instructors keep track of student activities and gives students an opportunity to know how they are performing by comparing their grades with other students through a game-like leader board interface, thus creating a competitive environment in the class. Contains source code.