Computer Sciences Commons^™

Multi-Branch Ensemble Learning Architecture Based On 3d Cnn For False Positive Reduction In Lung Nodule Detection, Haichao Cao, Hong Liu, Enmin Song, Chih-Cheng Hung

Faculty and Research Publications

It is critical to have accurate detection of lung nodules in CT images for the early diagnosis of lung cancer. In order to achieve this, it is necessary to reduce the false positive rate of detection. Due to the heterogeneity of lung nodules and their similarity to the background, it is difficult to distinguish true lung nodules from numerous candidate nodules. In this paper, in order to solve this challenging problem, we propose a Multi-Branch Ensemble Learning architecture based on the three-dimensional (3D) convolutional neural networks (MBEL-3D-CNN). The method combines three key ideas: 1) constructing a 3D-CNN to make the …

Web-Based Recommendation System For Smart Tourism: Multiagent Technology, Raheleh Hassannia, Ali Vatankhah Barenji, Zhi Li, Habib Alipour

Faculty and Research Publications

The purpose of the study is to design and develop a recommended system based on agent and web technologies, which utilizes a hybrid recommendation filtering for the smart tourism industry. A hybrid recommendation system based on agent technology is designed by considering the online communication with other sectors in the tourism industry, such as the tourism supply chain, agency etc. However, online communication between the sectors via agents is designed and developed based on the contract net protocol. Furthermore, the design system is developed on the java agent development framework and implemented as a web application. Case study-based results considering …

Pasnet: Pathway-Associated Sparse Deepneural Network For Prognosis Prediction From High-Throughput Data, Jie Hao, Youngsoon Kim, Tae-Kyung Kim, Mingon Kang

Faculty and Research Publications

Background: Predicting prognosis in patients from large-scale genomic data is a fundamentally challenging problem in genomic medicine. However, the prognosis still remains poor in many diseases. The poor prognosis maybe caused by high complexity of biological systems, where multiple biological components and their hierarchical relationships are involved. Moreover, it is challenging to develop robust computational solutions with high-dimension, low-sample size data. Results: In this study, we propose a Pathway-Associated Sparse Deep Neural Network (PASNet) that not only predicts patients’ prognoses but also describes complex biological processes regarding biological pathways for prognosis. PASNet models a multilayered, hierarchical biological system of genes …

Librarians' Perceptions Of Artificial Intelligence And Its Potential Impact On The Profession, Barbara A. Wood, David Evans

Faculty and Research Publications

The subject of artificial intelligence (AI) is being discussed everywhere in the media. Stephen Hawking, Elon Musk, and Bill Gates regularly sound the alarm about AI as an existential threat to humankind. Open a newspaper, turn on the television, or log on to the internet, and you will find a plethora of information and opinions on AI and its potential impact on human endeavors. In addition to being a hot topic in the media, the scholarly literature in medicine and law is replete with AI research. It acknowledges AI as a transformative, if not disruptive, game changer. AI is being …

Stable Solution To L 2,1-Based Robust Inductive Matrix Completion And Its Application In Linking Long Noncoding Rnas To Human Diseases, Ashis Kumer Biswas, Dongchul Kim, Mingon Kang, Chris Ding

Faculty and Research Publications

Backgrounds A large number of long intergenic non-coding RNAs (lincRNAs) are linked to a broad spectrum of human diseases. The disease association with many other lincRNAs still remain as puzzle. Validation of such links between the two entities through biological experiments are expensive. However, a plethora lincRNA-data are available now, thanks to the High Throughput Sequencing (HTS) platforms, Genome Wide Association Studies (GWAS), etc, which opens the opportunity for cutting-edge machine learning and data mining approaches to extract meaningful relationships among lincRNAs and diseases. However, there are only a few in silico lincRNA-disease association inference tools available to date, and …

Advanced Techniques For Computational And Information Sciences, William Guo, Chih-Cheng Hung, Paul Scheunders, Bor-Chen Kuo

Faculty and Research Publications

New techniques in computational and information sciences have played an important role in keeping advancing the so called knowledge economy. Advanced techniques have been introduced to or emerging in almost every field of the scientific world for hundreds of years, which has been accelerated since the late 1970s when the advancement in computers and digital technologies brought the world into the Information Era. In addition to the rapid development of computational intelligence and new data fusion techniques in the past thirty years [1–4], mobile and cloud computing, grid computing driven numeric computation models, big data intelligence, and other emerging technologies …

Informing And Performing: A Study Comparingadaptive Learning To Traditional Learning, Meg Coffin Murray, Jorge Perez

Faculty and Research Publications

Technology has transformed education, perhaps most evidently in course delivery options. However, compelling questions remain about how technology impacts learning. Adaptive learning tools are technology-based artifacts that interact with learners and vary presentation based upon that interaction. This study examines completion rates and exercise scores for students assigned adaptive learning exercises and compares them to completion rates and quiz scores for students assigned objective-type quizzes in a university digital literacy course. Current research explores the hypothesis that adapting instruction to an individual’s learning style results in better learning outcomes. Computer technology has long been seen as an answer to the …

Mobile Phishing Attacks And Mitigation Techniques, Hossain Shahriar, Tulin Klintic, Victor Clincy

Faculty and Research Publications

Mobile devices have taken an essential role in the portable computer world. Portability, small screen size, and lower cost of production make these devices popular replacements for desktop and laptop computers for many daily tasks, such as surfing on the Internet, playing games, and shopping online. The popularity of mobile devices such as tablets and smart phones has made them a frequent target of traditional web-based attacks, especially phishing. Mobile device-based phishing takes its share of the pie to trick users into entering their credentials in fake websites or fake mobile applications. This paper discusses various phishing attacks using mobile …

A Comparative Study Of Email Forensic Tools, Vamshee Krishna Devendran, Hossain Shahriar, Victor Clincy

Faculty and Research Publications

Over the last decades, email has been the major carrier for transporting spam and malicious contents over the network. Email is also the primary source of numerous criminal activities on the Internet. Computer Forensics is a systematic process to retain and analyze saved emails for the purpose of legal proceedings and other civil matters. Email analysis is challenging due to not only various fields that can be forged by hackers or malicious users, but also the flexibility of composing, editing, deleting of emails using offline (e.g., MS Outlook) or online (e.g., Web mail) email applications. Towards this direction, a number …

Drip - Data Rich, Information Poor: A Concise Synopsis Of Data Mining, Muhammad Obeidat, Max North, Lloyd Burgess, Sarah North

Faculty and Research Publications

As production of data is exponentially growing with a drastically lower cost, the importance of data mining required to extract and discover valuable information is becoming more paramount. To be functional in any business or industry, data must be capable of supporting sound decision-making and plausible prediction. The purpose of this paper is concisely but broadly to provide a synopsis of the technology and theory of data mining, providing an enhanced comprehension of the methods by which massive data can be transferred into meaningful information.

Developing Health Information Technology (Hit) Programs And Hit Curriculum: The Southern Polytechnic State University Experience, Chi Zhang, Han Reichgelt, Rebecca H. Rutherfoord, Andy Ju An Wang

Faculty and Research Publications

Health Information Technology (HIT) professionals are in increasing demand as healthcare providers need help in the adoption and meaningful use of Electronic Health Record (EHR) systems while the HIT industry needs workforce skilled in HIT and EHR development. To respond to this increasing demand, the School of Computing and Software Engineering at Southern Polytechnic State University designed and implemented a series of HIT educational programs. This paper summarizes our experience in the HIT curriculum development and provides an overview of HIT workforce development initiatives and major HIT and health information management (HIM) educational resources. It also provides instructional implications and …

Promoting Information Systems Major To Undergraduate Students - A Comprehensive Investigation, Lei Li, Chi Zhang, Guangzhi Zheng

Faculty and Research Publications

Weak enrollment growth has been a concern for many Information Systems (IS) programs in recent years although the IT/IS job market remains strong. Stimulating undergraduate students’ interest to IS programs have been a challenge. In this paper, the researchers took a comprehensive approach to study how to effectively promote a Management Information Systems (MIS) program to undergraduate students at a medium-size public university in the southeastern US. Using a survey-based method, the researchers first investigated the factors that impact students’ selection of majors and identified students’ perceptions on an MIS program. In this paper, an MIS program promotion strategy was …

Distributed And Asynchronous Data Collection In Cognitive Radio Networks With Fairness Consideration, Zhipeng Cai, Shouling Ji, Jing He, Lin Wei

Faculty and Research Publications

As a promising communication paradigm, Cognitive Radio Networks (CRNs) have paved a road for Secondary Users (SUs) to opportunistically exploit unused licensed spectrum without causing unacceptable interference to Primary Users (PUs). In this paper, we study the distributed data collection problem for asynchronous CRNs, which has not been addressed before. We study the Proper Carrier-sensing Range (PCR) for SUs. By working with this PCR, an SU can successfully conduct data transmission without disturbing the activities of PUs and other SUs. Subsequently, based on the PCR, we propose an Asynchronous Distributed Data Collection (ADDC) algorithm with fairness consideration for CRNs. ADDC …

Unraveling The Digital Literacy Paradox: How Higher Education Fails At The Fourth Literacy., Meg Coffin Murray, Jorge Perez

Faculty and Research Publications

Governments around the globe are recognizing the economic ramifications of a digitally literate citizenry and implementing systemic strategies to advance digital literacy. Awareness of the growing importance of digital literacy in today’s workplace coexists paradoxically with apparent foot-dragging on the part of many universities in assessment and amplification of these important competencies. This paper makes a case for digital literacy, presents models of the complex construct, and presents the results of a digital literacy assessment administered to students enrolled in a senior seminar course at a regional university in the United States. Reflection on the study results evoked our mantra …

Effective Detection Of Vulnerable And Malicious Browser Extensions, Hossain Shahriar, Komminist Weldemariam, Mohammad Zulkernine, Thibaud Lutellier

Faculty and Research Publications

Unsafely coded browser extensions can compromise the security of a browser, making them attractive targets for attackers as a primary vehicle for conducting cyber-attacks. Among others, the three factors making vulnerable extensions a high-risk security threat for browsers include: i) the wide popularity of browser extensions, ii) the similarity of browser extensions with web applications, and iii) the high privilege of browser extension scripts. Furthermore, mechanisms that specifically target to mitigate browser extension-related attacks have received less attention as opposed to solutions that have been deployed for common web security problems (such as SQL injection, XSS, logic flaws, client-side vulnerabilities, …

Analysis Of A Scholarly Social Networking Site: The Case Of The Dormant User, Meg Murray

Faculty and Research Publications

Many scholarly social networking sites targeting an audience of academicians and researchers have appeared on the Internet in recent years. Their vision is to change the way researchers connect, share and collaborate to solve real world problems. Despite the hype, however, their impact on higher education is unclear. Studies exist that address the benefits of these sites, but studies that investigate the implications of how scholarly social networking systems vet information, including data related to user profiles and uploaded content, is nonexistent. This paper chronicles the system management of user information for an inactive user of a scholarly social networking …

The Adoption Of E-Learning Systems In Low Income Countries: The Case Of Ethiopia, Yonas Hagos, Solomon Negash

Faculty and Research Publications

This paper presents the Technology Acceptance Model (TAM) to examine the adoption of e-learning system in low-income countries, the case of Ethiopia. The research uses a quantitative research approach to examine Ethiopian tertiary level distance students’ determinant factors for the acceptance of e-learning systems. A questionnaire-based survey was conducted to collect data from 255 undergraduate distance learners in a higher education institute in Ethiopia. The data were analyzed using the Structural Equation Modeling (SEM) (Hair et al, 2005) technique to examine the causal model. The results indicated that perceived usefulness and perceived ease of use significantly affected distance learners’ behavioral …

Rethinking Fs-Isac: An It Security Information Sharing Network Model For The Financial Services Sector, Charles Zhechao Liu, Humayun Zafar, Yoris A. Au

Faculty and Research Publications

This study examines a critical incentive alignment issue facing FS-ISAC (the information sharing alliance in the financial services industry). Failure to encourage members to share their IT security-related information has seriously undermined the founding rationale of FS-ISAC. Our analysis shows that many information sharing alliances’ membership policies are plagued with the incentive misalignment issue and may result in a “free-riding” or “no information sharing” equilibrium. To address this issue, we propose a new information sharing membership policy that incorporates an insurance option and show that the proposed policy can align members’ incentives and lead to a socially optimal outcome. Moreover, …

Hardware Components In Cybersecurity Education, Dan Chia-Tien Lo, Max North, Sarah North

Faculty and Research Publications

Hardware components have been designated as required academic content for colleges to be recognized as a center of academic excellence in cyber operations by the National Security Agency (NSA). To meet the hardware requirement, computer science and information technology programs must cover hardware concepts and design skills, topics which are less emphasized in existing programs. This paper describes a new pedagogical model for hardware based on network intrusion detection taught at college and graduate levels in a National Center of Academic Excellence in Information Assurance Education Program (CAE/IAE). The curriculum focuses on the fundamental concepts of network intrusion detection mechanisms, …

A Comparative Review Of Information Technology Project Management In Private And Public Sector Organization, Muhammad Obeidat, Max North

Faculty and Research Publications

Both private and public sector organizations tend to recognize the prominence of information technology within project management techniques and practices. The primary objective of this paper is to present a comparative review of information technology within project management in private and public sectors. Moreover, this research provides an extensive review of related topics such as the evolution of information technology, factors contributing to project abandonment, and the tools and techniques of management that effect project success. In conclusion, the authors present a variety of practical and effective guidelines and recommend approaches for the successful deployment of information technology within project …

Student Interaction With Content In Online And Hybrid Courses: Leading Horses To The Proverbial Water, Meg Murray, Jorge Perez, Debra Geist, Alison Hedrick

Faculty and Research Publications

Permutations of traditional and online learning are rapidly advancing along a blended continuum, prompting conjecture that learning and e-learning will soon be indistinguishable. As variations of blended learning evolve, educators worldwide must develop better understanding of how effective interaction with course content impacts engagement and learning. This study compares patterns of access to instructional content in online and hybrid courses offered at a regional university in the United States. Frequency counts and access rates were examined for course content in four categories: core materials, direct support, indirect support, and ancillary materials. Observed results were echoed in responses to a survey …

Area Query Processing Based On Gray Code In Wireless Sensor Networks, Chunyu Ai, Yueming Duan, Mingyuan Yan, Jing He

Faculty and Research Publications

Area query processing is significant for various applications of wireless sensor networks since it can request information of particular areas in the monitored environment. Existing query processing techniques cannot solve area queries. Intuitively centralized processing on Base Station can accomplish area queries via collecting information from all sensor nodes. However, this method is not suitable for wireless sensor networks with limited energy since a large amount of energy is wasted for reporting useless data. This motivates us to propose an energy-efficient in-network area query processing scheme. In our scheme, the monitored area is partitioned into grids, and a unique gray …

Hypotheses Generation As Supervised Link Discovery With Automated Class Labeling On Large-Scale Biomedical Concept Networks, Jayasimha R. Katukuri, Ying Xie, Vijay Raghavan, Ashish Gupta

Faculty and Research Publications

Computational approaches to generate hypotheses from biomedical literature have been studied intensively in recent years. Nevertheless, it still remains a challenge to automatically discover novel, cross-silo biomedical hypotheses from large-scale literature repositories. In order to address this challenge, we first model a biomedical literature repository as a comprehensive network of biomedical concepts and formulate hypotheses generation as a process of link discovery on the concept network. We extract the relevant information from the biomedical literature corpus and generate a concept network and concept-author map on a cluster using Map-Reduce framework. We extract a set of heterogeneous features such as random …

An Approach To Nearest Neighboring Search For Multi-Dimensional Data, Yong Shi, Li Zhang, Lei Zhu

Faculty and Research Publications

Finding nearest neighbors in large multi-dimensional data has always been one of the research interests in data mining field. In this paper, we present our continuous research on similarity search problems. Previously we have worked on exploring the meaning of K nearest neighbors from a new perspective in PanKNN [20]. It redefines the distances between data points and a given query point Q, efficiently and effectively selecting data points which are closest to Q. It can be applied in various data mining fields. A large amount of real data sets have irrelevant or obstacle information which greatly affects the effectiveness …

A Call To Is Educators To Respond To The Voices Of Women In Information Security, Amy B. Woszczynski, Sherri Shade

Faculty and Research Publications

Much prior research has examined the dearth of women in the IT industry. The purpose of this study is to examine the perceptions of women in IT within the context of information security and assurance. This paper describes results from a study of a relatively new career path to see if there are female-friendly opportunities that have not existed in previous IT career paths. Research methodology focuses on a qualitative analysis of in-depth interviews with women who are self-described information security professionals. A primary goal of the study is to understand the perceptions of women in information security and determine …

Analysis Of Xbrl Literature: A Decade Of Progress And Puzzle, Saeed Roohani, Zhao Xianming, Ernest Capozzoli, Barbara Lamberton

Faculty and Research Publications

XBRL (eXtensible Business Reporting language) was recently, in 2008, in its 10th year. The concept was articulated in 1998 by Charles Hoffman, known as XFRML (eXtensible Financial Reporting Mark Up Language) to facilitate the business reporting process and improve financial reporting. The objective of this paper is to examine a decade (1998-2008) of XBRL articles published in various publications including trade, practitioner and academic journals to identify trends and patterns, milestones, and organizations actively contributed to this development. Another goal is to assess public perceptions of XBRL, its capabilities and its future. We examined published articles where XBRL appeared either …

An Attempt To Find Neighbors, Yong Shi, Ryan Rosenblum

Faculty and Research Publications

In this paper, we present our continuous research on similarity search problems. Previously we proposed PanKNN[18]which is a novel technique that explores the meaning of K nearest neighbors from a new perspective, redefines the distances between data points and a given query point Q, and efficiently and effectively selects data points which are closest to Q. It can be applied in various data mining fields. In this paper, we present our approach to solving the similarity search problem in the presence of obstacles. We apply the concept of obstacle points and process the similarity search problems in a different way. …

Biomedical Relationship Extraction From Literature Based On Bio-Semantic Token Subsequences, Ying Xie, Jayasimha R. Katukuri, Vijay V. Raghavan

Faculty and Research Publications

Relationship Extraction (RE) from biomedical literature is an important and challenging problem in both text mining and bioinformatics. Although various approaches have been proposed to extract protein?protein interaction types, their accuracy rates leave a large room for further exploring. In this paper, two supervised learning algorithms based on newly defined "bio-semantic token subsequence" are proposed for multi-class biomedical relationship classification. The first approach calculates a "bio-semantic token subsequence kernel", whereas the second one explicitly extracts weighted features from bio-semantic token subsequences. The two proposed approaches outperform several alternatives reported in literature on multi-class protein?protein interaction classification.

Database Security: What Students Need To Know, Meg C. Murray

Faculty and Research Publications

Database security is a growing concern evidenced by an increase in the number of reported incidents of loss of or unauthorized exposure to sensitive data. As the amount of data collected, retained and shared electronically expands, so does the need to understand database security. The Defense Information Systems Agency of the US Department of Defense (2004), in its Database Security Technical Implementation Guide, states that database security should provide controlled, protected access to the contents of a database as well as preserve the integrity, consistency, and overall quality of the data. Students in the computing disciplines must develop an …

Object Oriented Program Correctness With Oosiml, José M. Garrido

Faculty and Research Publications

Software reliability depends on program correctness and robustness and these are extremely important in developing high-quality software. Correctness is also essential when considering aspects of software security. However, experience applying these concepts, associated methods, and supporting software with Eiffel and Java have shown that students find some diffculty learning program correctness and in learning the software tools provided. We have developed an experimental language, OOSimL, that includes an assertion notation similar to that of Eiffel but which has much more flexibility, and that provides the same semantics as Java.

The first part of this paper provides an overview of concepts …