Physical Sciences and Mathematics Commons^™

The Critical Role Of Cubesat Spacecraft In A Multi-Tier Mission For Mars Exploration, Jeremy Straub

Jeremy Straub

A multi-tier architecture is under development (with similar craft heterogeneity to Fink's work on ‘tier scalable’ missions) which will facilitate autonomous local control of multiple heterogeneous craft. This mission architecture has been developed with a Mars mission in mind and has included CubeSats in a variety of critical mission roles.

Two concepts will be presented: the addition of CubeSats to a larger-scale multi-tier mission, where the CubeSats serve a supporting role and a mission driven by CubeSat orbital capabilities. In the first, CubeSats are utilized to augment the area of spatial coverage that can be obtained and the temporal coverage …

Context-Aware Spelling Corrector For Sentiment Analysis, Dr. Muhammad Zubair Asghar, Fazal Masud Kundi

Dr. Muhammad Zubair Asghar

One of the most thrived features of the Web 2.0 era is the fastest growing of user-generated content in the shape of blogs and reviews, with unmatched speed and size. These reviews contain poor, text quality and structure which results spelling mistakes as well as out-of-vocabulary words. This paper presents a Context-Aware Spelling Corrector for Sentiment Analysis based on similarity measures and statistical language model. The paper also presents some compelling statistics about spelling errors. The comparative results show that the proposed framework outperforms the related systems, features wise and in accuracy.

Lexicon-Based Sentiment Analysis In The Social Web, Fazal Masud Kundi, Dr. Muhammad Zubair Asghar

Dr. Muhammad Zubair Asghar

Sentiment analysis is a compelling issue for both information producers and consumers. We are living in the “age of customer”, where customer knowledge and perception is a key for running successful business. The goal of sentiment analysis is to recognize and express emotions digitally. This paper presents the lexicon-based framework for sentiment classification, which classifies tweets as a positive, negative, or neutral. The proposed framework also detects and scores the slangs used in the tweets. The comparative results show that the proposed system outperforms the existing systems. It achieves 92% accuracy in binary classification and 87% in multi-class classification.

Lexicon Based Approach For Sentiment Classification Of User Reviews, Dr. Muhammad Zubair Asghar

Dr. Muhammad Zubair Asghar

With the advent of web, online user reviews are getting more and more attention of the researchers because valuable information about products and services are available on social media like twitter1. These reviews are very helpful for organizations as well as for new customers showing interest in these products or services. But this data is generated in tremendous amount which is out of control of manual mining methods. These reviews need a model that has the ability to gauge these shared reviews according to predefined categories. This work introduces a rule based approach to find the opinion classification of reviews. …

Darwin: A Ground Truth Agnostic Captcha Generator Using Evolutionary Algorithm, Eric Y. Chen, Lin-Shung Huang, Ole J. Mengshoel, Jason D. Lohn

Ole J Mengshoel

Feedback Control For Multi-Modal Optimization Using Genetic Algorithms, Jun Shi, Ole J. Mengshoel, Dipan K. Pal

Ole J Mengshoel

From Question Context To Answer Credibility: Modeling Semantic Structures For Question Answering Using Statistical Methods, Protima Banerjee, Hyoil Han

Hyoil Han

Within a Question Answering (QA) framework, Question Context plays a vital role. We define Question Context to be background knowledge that can be used to represent the user’s information need more completely than the terms in the query alone. This paper proposes a novel approach that uses statistical language modeling techniques to develop a semantic Question Context which we then incorporate into the Information Retrieval (IR) stage of QA. Our approach proposes an Aspect-Based Relevance Language Model as basis of the Question Context Model. This model proposes that the sparse vocabulary of a query can be supplemented with semantic information …

A Computationally Efficient System For High-Performance Multi-Document Summarization, Sean Sovine, Hyoil Han

Hyoil Han

We propose and develop a simple and efficient algorithm for generating extractive multi-document summaries and show that this algorithm exhibits state-of-the-art or near state-of-the-art performance on two Document Understanding Conference datasets and two Text Analysis Conference datasets. Our results show that algorithms using simple features and computationally efficient methods are competitive with much more complex methods for multi-document summarization (MDS). Given these findings, we believe that our summarization algorithm can be used as a baseline in future MDS evaluations. Further, evidence shows that our system is near the upper limit of performance for extractive MDS.

Language Modeling Approaches To Information Retrieval, Protima Banerjee, Hyoil Han

Hyoil Han

This article surveys recent research in the area of language modeling (sometimes called statistical language modeling) approaches to information retrieval. Language modeling is a formal probabilistic retrieval framework with roots in speech recognition and natural language processing. The underlying assumption of language modeling is that human language generation is a random process; the goal is to model that process via a generative statistical model. In this article, we discuss current research in the application of language modeling to information retrieval, the role of semantics in the language modeling framework, cluster-based language models, use of language modeling for XML retrieval and …

Direct Neighbor Search, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang

Kyriakos MOURATIDIS

In this paper we study a novel query type, called direct neighbor query. Two objects in a dataset are direct neighbors (DNs) if a window selection may exclusively retrieve these two objects. Given a source object, a DN search computes all of its direct neighbors in the dataset. The DNs define a new type of affinity that differs from existing formulations (e.g., nearest neighbors, nearest surrounders, reverse nearest neighbors, etc.) and finds application in domains where user interests are expressed in the form of windows, i.e., multi-attribute range selections. Drawing on key properties of the DN relationship, we develop an …

Clustering Of Search Trajectory And Its Application To Parameter Tuning, Linda Lindawati, Hoong Chuin Lau, David Lo

David LO

This paper is concerned with automated classification of Combinatorial Optimization Problem instances for instance-specific parameter tuning purpose. We propose the CluPaTra Framework, a generic approach to CLUster instances based on similar PAtterns according to search TRAjectories and apply it on parameter tuning. The key idea is to use the search trajectory as a generic feature for clustering problem instances. The advantage of using search trajectory is that it can be obtained from any local-search based algorithm with small additional computation time. We explore and compare two different search trajectory representations, two sequence alignment techniques (to calculate similarities) as well as …

Budgeted Personalized Incentive Approaches For Smoothing Congestion In Resource Networks, Pradeep Varakantham, Na Fu, William Yeoh, Shih-Fen Cheng, Hoong Chuin Lau

Shih-Fen CHENG

Congestion occurs when there is competition for resources by sel sh agents. In this paper, we are concerned with smoothing out congestion in a network of resources by using personalized well-timed in- centives that are subject to budget constraints. To that end, we provide: (i) a mathematical formulation that computes equilibrium for the re- source sharing congestion game with incentives and budget constraints; (ii) an integrated approach that scales to larger problems by exploiting the factored network structure and approximating the attained equilib- rium; (iii) an iterative best response algorithm for solving the uncon- strained version (no budget) of the …

Multi-Agent Orienteering Problem With Time-Dependent Capacity Constraints, Cen Chen, Shih-Fen Cheng, Hoong Chuin Lau

Shih-Fen CHENG

The Orienteering Problem (OP), as originally defined by Tsiligirides, is the problem of cross-countr sport in which participants get rewards from visiting a predefined set of checkpoints. As Orienteering Problem can be used to describe a wide variety of real-world problems like route planning for facility inspection, patrolling of strategic location, and reward-weighted traveling salesman problem, it has attracted continuous interests from researchers and a large number of variants and corresponding algorithms for solving them have been introduced.

Mechanisms For Arranging Ride Sharing And Fare Splitting For Last-Mile Travel Demands, Shih-Fen Cheng, Duc Thien Nguyen, Hoong Chuin Lau

Shih-Fen CHENG

A great challenge of city planners is to provide efficient and effective connection service to travelers using public transportation system. This is commonly known as the last-mile problem and is critical in promoting the utilization of public transportation system. In this paper, we address the last-mile problem by considering a dynamic and demand-responsive mechanism for arranging ride sharing on a non-dedicated commercial fleet (such as taxis or passenger vans). Our approach has the benefits of being dynamic, flexible, and with low setup cost. A critical issue in such ride-sharing service is how riders should be grouped and serviced, and how …

A Multi-Objective Memetic Algorithm For Vehicle Resource Allocation In Sustainable Transportation Planning, Hoong Chuin Lau, Lucas Agussurja, Shih-Fen Cheng, Pang Jin Tan

Shih-Fen CHENG

Sustainable supply chain management has been an increasingly important topic of research in recent years. At the strategic level, there are computational models which study supply and distribution networks with environmental considerations. At the operational level, there are, for example, routing and scheduling models which are constrained by carbon emissions. Our paper explores work in tactical planning with regards to vehicle resource allocation from distribution centers to customer locations in a multi-echelon logistics network. We formulate the bi-objective optimization problem exactly and design a memetic algorithm to efficiently derive an approximate Pareto front. We illustrate the applicability of our approach …

An Agent-Based Simulation Approach To Experience Management In Theme Parks, Shih-Fen Cheng, Larry Junjie Lin, Jiali Du, Hoong Chuin Lau, Pradeep Reddy Varakantham

Shih-Fen CHENG

In this paper, we illustrate how massive agent-based simulation can be used to investigate an exciting new application domain of experience management in theme parks, which covers topics like congestion control, incentive design, and revenue management. Since all visitors are heterogeneous and self-interested, we argue that a high-quality agent-based simulation is necessary for studying various problems related to experience management. As in most agent-base simulations, a sound understanding of micro-level behaviors is essential to construct high-quality models. To achieve this, we designed and conducted a first-of-its-kind real-world experiment that helps us understand how typical visitors behave in a theme-park environment. …

Interacting Knapsack Problem In Designing Resource Bundles, Truong Huy D. Nguyen, Pradeep Reddy Varakantham, Hoong Chuin Lau, Shih-Fen Cheng

Shih-Fen CHENG

In many real-life businesses, the service provider/seller keeps a log of the visitors’ behavior as a way to assess the efficiency of the current business/operation model and find room for improvement. For example, by tracking when visitors entering attractions in a theme park, theme park owners can detect when and where congestion may occur, thus having contingency plans to reroute the visitors accordingly. Similarly, a Cable TV service provider can track channel switching events at each household to identify uninteresting channels. Subsequently, the repertoire of channels up for subscription can evolve over time to better serve the entertainment demand of …

Detection And Scoring Of Internet Slangs For Sentiment Analysis Using Sentiwordnet, Dr. Muhammad Zubair Asghar

Dr. Muhammad Zubair Asghar

The online information explosion has created great challenges and opportunities for both information producers and consumers. Understanding customer’s feelings, perceptions and satisfaction is a key performance indicator for running successful business. Sentiment analysis is the digital recognition of public opinions, feelings, emotions and attitudes. People express their views about products, events or services using social networking services. These reviewers excessively use Slangs and acronyms to express their views. Therefore, Slang's analysis is essential for sentiment recognition. This paper presents a framework for detection and scoring of Internet Slangs (DSIS) using SentiWordNet in conjunction with other lexical resources. The comparative results …

Sentiment Classification Through Semantic Orientation Using Sentiwordnet, Dr. Muhammad Zubair Asghar, Dr, Auranzeb Khan

Dr. Muhammad Zubair Asghar

Sentiment analysis is the procedure by which information is extracted from the opinions, appraisals and emotions of people in regards to entities, events and their attributes. In decision making, the opinions of others have a significant effect on customers ease in making choices regards to online shopping, choosing events, products, entities. In this paper, a rule based domain independent sentiment analysis method is proposed. The proposed method classifies subjective and objective sentences from reviews and blog comments. The semantic score of subjective sentences is extracted from SentiWordNet to calculate their polarity as positive, negative or neutral based on the contextual …

Lexical Based Semantic Orientation Of Online Customer Reviews And Blogs-J-Am Sci 10(8) 143_147--07-June-2014.Pdf, Dr. Muhammad Zubair Asghar

Dr. Muhammad Zubair Asghar

Rapid increase in internet users along with growing power of online review sites and social media hasgiven birth to sentiment analysis or opinion mining, which aims at determining what other people think andcomment. Sentiments or Opinions contain public generated content about products, services, policies and politics.People are usually interested to seek positive and negative opinions containing likes and dislikes, shared by users forfeatures of particular product or service. This paper proposed sentence-level lexical based domain independentsentiment classification method for different types of data such as reviews and blogs. The proposed method is basedon general lexicons i.e. WordNet, SentiWordNet and user …

Of Mills And Machines - Computing Thought Experiments On Consciousness, Aïda Raoult

Aïda Raoult

In this computing-oriented analysis, 5 of the most influential thought experiments on consciousness inspired by the development of A.I. in the 70s-80s are (1) presented as more refined versions of Leibniz’s mill (LM), (2) then reformulated in terms of LM which reveals a divergence in their approach of the mind-body problem; (3) combining this result with computational complexity theory shows the ontological question is less difficult to answer than the causal one. In the end, (4) these considerations participate in the debate over machine consciousness.

Constraint Satisfaction Problem: A Generic Scheduler, Ben Carpenter, Brent Weichel, Jeremy Straub, Eunjin Kim

Jeremy Straub

The task was to create a scheduler that would create a schedule that gets as many of the tasks done as possible while maximizing the total value of the tasks performed. Each task was assigned a value, a priority, and a duration. Each task also had certain times that they could be run, so they couldn’t just be run at any point where they fit. We decided that in order to get a more accurate ordering for the process, we would take the value divided by the duration that way we were less likely to skip over processes that ran …

Dynamic Task Scheduling Problem: Greedy Knapsack Solution, Christian Sandtveit, Darrin Winger, Jeremy Straub, Eunjin Kim

Jeremy Straub

The problem that we worked with was a dynamic scheduling problem. For this problem, we are given a set of tasks to be scheduled in an allotted time slot, so that the total value of the tasks done is maximized. Each task has a duration, value. Each task also has one or more periods in which they can be scheduled. Some tasks can have conflicting time slots that can prevent other tasks from being scheduled. As tasks are assigned time slots it is possible to prevent other tasks from being as-signed a time slot. Looking for ways to minimize the …

Medical Rate Setting: Multi-Curve Approximation And Projection, Darrin Winger, Christian Sandtveit, Jeremy Straub, Eunjin Kim

Jeremy Straub

In order to maximize profit, our approach was to maximize the difference between total revenue and total cost, where total revenue would be larger than total cost. In the problem we are given a series of points, which relates price, cost, profit and quantity. We can calculate the total revenue by multi-plying the price with quantity, and the total cost by multiplying the cost with the quantity. Total profit is calculated by multiplying profit and quantity. We are given 4 initial points, and based on those 4 points we will calculate the point where the profit is currently maximized. Based …

Task Scheduling Problem: Using The Most Constrained Variable Algorithm To Maximize, Jaeden Lovin, Calvin Bina, Jeremy Straub, Eunjin Kim

Jeremy Straub

For this constraint satisfaction problem we needed to schedule a series of tasks to run in a certain order. Each task has a set duration that it must run for and a domain of times during which it can run during. Each task had a value and the goal of the problem was to pick times for the tasks to run in or-der to maximize the total value. We thought of multiple ways to potentially approach this problem, and decided to use some form of the least constraining variable. We would choose the task with the least constraints on other …

Medical Rate Setting Problem: Using The Hill-Climbing Search To Maximize Health Care Provider Profit, Calvin Bina, Jaeden Lovin, Jeremy Straub, Eunjin Kim

Jeremy Straub

Our program for calculating the optimal price for a service is relatively simple, but it gets great results. We make use of quadratic regres-sion. Quadratic regression has a very similar concept to linear regression. Given a set of data points, we find the equation that is the best fit to represent those data points. With linear re-gression, our resulting equation is linear. How-ever, with quadratic regression, our end result is a quadratic equation. We have two quadratic equations to come up with. One is our cost function and the other is our units sold func-tion. Both of these equations are …

Update On The Operating Software For Openorbiter, Dayln Limesand, Christoffer Korvald, Jeremy Straub, Ronald Marsh

Jeremy Straub

The operating software team of the OpenOrbiter project has been tasked with developing software for general spacecraft maintenance, performing mission tasks and the monitoring of system critical aspects of the spacecraft. To do so, the team is developing an autonomous system that will be able to continuously check sensors for data, and schedule tasks that pertain to the current mission and general maintenance of the onboard systems. Development in support of these objectives is ongoing with work focusing on the completion of the development of a stable system. This poster presents an overview of current work on the project and …

The Use Of The Blackboard Architecture For A Decision Making System For The Control Of Craft With Various Actuator And Movement Capabilities, Jeremy Straub, Hassan Reza

Jeremy Straub

This paper provides an overview of an approach to the control of multiple craft with heterogeneous movement and actuation characteristics that is based on the Blackboard software architecture. An overview of the Blackboard architecture is provided. Then, the operational and mission requirements that dictate the need for autonomous control are characterized and the utility of the Blackboard architecture is for meeting these requirements is discussed. The performance of a best-path solver and naïve solver are compared. The results demonstrate that the best-path solver outperforms the naïve solver in the amount of time taken to generate a solution; however, the number …

Openorbiter Operating Software, Dayln Limesand, Christoffer Korvald, Jeremy Straub, Ronald Marsh

Jeremy Straub

The operating software team of the OpenOrbiter project has been tasked with developing software for general spacecraft maintenance, performing mission tasks and the monitoring of system critical aspects of the spacecraft. To do so, the team is developing an autonomous system that will be able to continuously check sensors for data, and schedule tasks that pertain to the current mission and general maintenance of the onboard systems. Development in support of these objectives is ongoing with work focusing on the completion of the development of a stable system. This poster will present an overview of current work on the project …

A Hybrid Prognostic Model For Oral Cancer Based On Clinicopathologic And Genomic Markers, Sameem Abdul Kareem

Sameem Abdul Kareem

There are very few prognostic studies that combine both clinicopathologic and genomic data. Most of the studies use only clinicopathologic factors without taking into consideration the tumour biology and molecular information, while some studies use genomic markers or microarray information only without the clinicopathologic parameters. Thus, these studies may not be able to prognoses a patient effectively. Previous studies have shown that prognosis results are more accurate when using both clinicopathologic and genomic data. The objectives of this research were to apply hybrid artificial intelligent techniques in the prognosis of oral cancer based on the correlation of clinicopathologic and genomic …