Computer Sciences Commons^™

Combining Micro And Macro Features For Online Pattern-Of-Life Movement Prediction, Shiau Hong Lim, Hasan Poonawala, Laura Wynter

Research Collection School Of Computing and Information Systems

We investigate the problem of predicting the future location of mobile objects, such as vehicles, ships, or people, in real time with a high degree of accuracy. Our premise is that an effective combination of recent and long-term historical data can significantly improve prediction performance by enabling a representation of the patterns-of-life of the objects. However, finding a feature representation that captures the long-term observed history of the objects in a compact yet informative manner is a key challenge in data mining and machine learning. To this end, we propose to combine “micro” features, which capture recent fine-grained trends, with …

Artificial Intelligence And The Challenge For Rural Medicine, James Denvir

Marshall Journal of Medicine

Recent advances in artificial intelligence, machine learning, and deep learning are beginning to have an impact on everyday experiences, from natural language processing used in automated telephone call centers to semi-autonomous vehicles. These techniques have also been applied to medical care. In this editorial we discuss applications of AI to medicine and argue for a proactive approach to include rural medicine in this paradigm shift.

Read And Publish: What Can Libraries Expect?, Josh Horowitz

Charleston Library Conference

The author provides a publisher's perspective on the challenges and opportunities faced by a mid-sized society in navigating the current transition to open access licensing models.

Data Curation Workshop: Tips And Tools For Today, Matthew M. Benzing

Charleston Library Conference

The current state of research data is like a disorganized photo collection: a mix of formats scattered across different media without a lot of authority control. That is changing as the need to make data available to researchers across the world is becoming recognized. Researchers know that their data needs to be maintained and made accessible, but often they do not have the time or the inclination to get involved in all of the details. This provides an excellent opportunity for librarians. Data curation is the process of preparing data to be made available in a repository with the goal …

Deepcon-Pre: Improved Protein Contact Map Prediction Using Inverse Covariance And Deep Residual Networks, Nachammai Palaniappan

Theses

As with most domains where machine learning methods are applied, correct feature engineering is critical when developing deep learning algorithms for solving the protein folding problem. Unlike the domains such as computer vision and natural language processing, feature engineering is not rigorously studied towards solving the protein folding problem. A recent research has highlighted that input features known as precision matrix are most informative for predicting inter-residue contact map, the key for building three-dimensional models. In this work, we study the significance of the precision matrix feature when very deep residual networks are trained. Using a standard dataset of 3456 …

Detecting Digitally Forged Faces In Online Videos, Neilesh Sambhu

USF Tampa Graduate Theses and Dissertations

We use Rossler’s FaceForensics dataset of 1004 online videos and their corresponding forged counterparts [1] to investigate the ability to distinguish digitally forged facial images from original images automatically with deep learning. The proposed convolutional neural network is much smaller than the current state-of-the-art solutions. Nevertheless, the network maintains a high level of accuracy (99.6%), all while using the entire FaceForensics dataset and not including any temporal information. We implement majority voting and show the impact on accuracy (99.67%), where only 1 video of 300 is misclassified. We examine why the model misclassified this one video. In terms of tuning …

Interactive Fitness Domains In Competitive Coevolutionary Algorithm, Atm Golam Bari

USF Tampa Graduate Theses and Dissertations

Evolutionary Algorithms (EA) have been successfully applied to a wide range of optimization and search problems where no mathematical model of the quality of a candidate solution is available. Interactive Evolutionary Algorithms (IEA) and Competitive Coevolutionary Algorithms (CCoEA) go one step further by being able to tackle problems where the only means to evaluate the quality of a candidate solution is via interactions. In a typical IEA, interactions take place between the solution being evolved and human evaluators. In a CCoEA, interactions take place between solutions themselves, without need for human interaction. This dissertation identifies computer-aided learning as an application …

Guest Editorial, Jiju Anthony, Chad Laux, Beth Cudney

Computer Information Technology Faculty Publications

No abstract provided.

Classifying Fiction And Non-Fiction Works Using Machine Learning, Rachna Gupta '21

Student Publications & Research

The objective of this project was to create a program that can determine whether an unknown text is a work of fiction or non-fiction using machine learning. Various datasets of speeches, ebooks, poems, scientific papers, and texts from Project Gutenberg and the Wolfram Example Data were utilized to train and test a Markov Chain machine learning model. A microsite was deployed with the final product that returns a probability of fictionality based on input from the user with 95% accuracy.

Digital Addiction: A Conceptual Overview, Amarjit Kumar Singh, Pawan Kumar Singh

Library Philosophy and Practice (e-journal)

Abstract

Digital addiction referred to an impulse control disorder that involves the obsessive use of digital devices, digital technologies, and digital platforms, i.e. internet, video game, online platforms, mobile devices, digital gadgets, and social network platform. It is an emerging domain of Cyberpsychology (Singh, Amarjit Kumar and Pawan Kumar Singh; 2019), which explore a problematic usage of digital media, device, and platforms by being obsessive and excessive. This article analyses, reviewed the current research, and established a conceptual overview on the digital addiction. The research literature on digital addiction has proliferated. However, we tried to categories the digital addiction, according …

Deep Neural Network Based Iterative Self-Taught Learning On Text Mining, Xiangwen Liu

Theses and Dissertations

[Motivation] Machine learning and deep learning models is the main methodology for discovering hidden knowledge of data. Data plays a significant role in the training process. However, lack of data especially labeled data is precious due to accessibility and high cost. How to use the abundant unlabeled data to enhance the downstream learning process on labeled data is an urgent task in machine learning and pattern recognition. [Methods] An STL (Self-taught learning) model is proposed in this dissertation, which can successfully learn features from downloaded unlabeled text and enhance the downstream tasks on labeled text. In addition, DLI-IT (Drug labeling …

On Automation Of Code Transformations For Concept Inventory Misconceptions, Dmytro Vitel

USF Tampa Graduate Theses and Dissertations

Identifying common misconceptions held by novice programmers is a primary goalof the Computing Education Research agenda. This thesis proposes to formalize such mis-conceptions through program transformations. We first describe the implementation of theEvoParsons system, that allows students to practice programming skills with the help ofso-called Parsons puzzles. This software serves as a tool for gathering data on how studentsinteract with such puzzles. Our first contribution is the system architecture reorganization:development of Web SPA UI, REST service back-end, hypothesis validation infrastructureand student-UI data collection. We then review and compare several code-transformationtools (ANTLR, Rascal MPL and StrategoXT) and show how they might …

Ai Leverage In Easing The 5g Complexity And Enhancing 5g Intelligent Connectivity, Xhafer Krasniqi

UBT International Conference

As 5G era is approaching fast and pre-commercial 5G tests and trials are happening everywhere around the world, one of the key challenges for carriers and 5G providers is to maintain and operate the network complexity required to meet diverse services and personalized user experience requirements. This maintenance and operation have to be smarter and more agile in 5G than it was in previous generations. AI and ML can be leveraged in this case to ease 5G complexity and at the same time enhance the intelligent connectivity between diverse devices and diverse tiny end points, e.g. IoT sensors.

Machine learning …

Password Typo Correction Using Discrete Logarithms, Nikola K. Blanchrad

UBT International Conference

As passwords remain the main online authentication method, focus has shifted from naive entropy to how usability improvements can increase security. Chatterjee et al. recently introduced the first two typotolerant password checkers, which improve usability at no security cost but are technically complex. We look at the more general problem of computing an edit distance between two strings without having direct access to those strings — by storing the equivalent of a hash. We propose a simpler algorithm for this problem that is asymptotically quasi-optimal in both bits stored and exchanged, at the cost of more computation on the server.

Vulnerability Of Passwords Consisting Of Numerical Repetitive Sequences In The Wpa2 Protocol, Genc Kelmendi, Edmond Hajrizi

UBT International Conference

Protocols that govern wireless security WPA2/WPA have been proven much more secure in comparison to their predecessor WEP. However, the human factor jeopardizes the solidity of cryptography by implementing passwords consisting of programmatically predictable numerical structures such as 1234512345, 11114444, 999888777 and so on. This practice endangers the security of the WPA protocol in particular, as the locally stored WPA handshake can be attacked for an unlimited number of times using brute-force attacks. The methods presented in this paper are effective in decrypting such passwords within seconds using ordinary processor power. The prevalence of this vulnerable practice in the Prishtina …

Establishing An Analytics Capability Within Hr, Rizwan Khan

River Cities Industrial and Organizational Psychology Conference

With advancements in technology, HR finally has the tools available to collect and process people data. But is that all that is needed to successfully implement and sustain an analytics capability within HR? The purpose of this presentation/tutorial is to demonstrate a realistic journey The AES Corporation has taken thus far in developing its People Analytics capability. A framework for the implementation of People Analytics will be presented which incorporates themes in I/O Psychology that have been incorporated into the framework such as goal setting theory, job analysis, and change management. How this framework is operationalized will also be demonstrated …

Improvement Of Gender Recognition Using The Cosfire Filter Framework (Simulations Platform Of Shape-Preserving Regression – Pchip), Virtyt Lesha, Arben Haveri, Jozef Bushati

UBT International Conference

Biometrics is evolving every day more and more in technical sense and consequently faces with further challenges that become sharper. One of these challenges of is gender recognition that finds very important and key applications. In this paper, we consider the gender recognition process implemented through the Cosfire filter applied through Viola-Jones algorithm and simulated through the Matlab platform. Objective of this paper is improving the execution of gender recognition. The database contains 237 images of 128 to 128 pixels, where 128 are males and 109 are females. For each of them, gender recognition is performed by applying current and …

Analyzing The Linearity Of Some Operators, Faton Kabashi, Azir Jusufi, Hizer Leka

UBT International Conference

Linear operators occupy an important place in functional analysis and linear algebra, which are among the most important and substantive disciplines of mathematics, whose methods and results have created an indispensable apparatus for the development of numerical mathematics, theory of approximations, equations differential and especially mathematical physics and applied mathematics. Also, linear operators are a central object of study in vector space theory.

A linear operator is a function which satisfies the conditions of additivity and homogeneity. Not every function is linear operators. We will try to explore some functions which are also linear operators.

An Overview Of Big Data Analytics In Banking: Approaches, Challenges And Issues, Fisnik Doko, Igor Miskovski

UBT International Conference

Banks are harnessing the power of Big Data. They use Big Data and Data Science to drive change towards data and analytics to gain an overall competitive advantage. The Big Data has potential to transform enterprise operations and processes especially in the banking sector, because they have huge amount of transaction data. The goal of this paper is to give an overview of different approaches and challenges that exists in Big Data in banking sector. The work presented here will fulfill the gap of research papers in the last five years, with focus on Big Data in central banks and …

How Do Kosovo Firms Utilize Business Intelligence? An Exploratory Study, Ardian Hyseni

UBT International Conference

The purpose of this paper is to examine how Kosovo firms utilize business intelligence to analyze their data and better understand the past, present and the future of their firm. Business intelligence offers firms the ability to analyze large amount of data quicker and more effective. Decision making has become easier with the use of BI tools, but making the right decision at right time has become vital for the firms performance. This research will contribute on business industry by providing evidence how Kosovo firms utilize the BI system, what BI tools and what business values and processes BI offers …

Applying Soa Approach To Financial Institution: Case Study, Agon Memeti, Florinda Imeri

UBT International Conference

A financial institution is an institution that conducts financial transactions, such as depositing money, taking out loans and/or exchanging currencies. Systems used by them like any other system tend to skew old, but, the replacement and integration of these systems is a difficult due to the heterogeneous nature. Due to this it is imperative to consider alternative infrastructure such as SOA (service-oriented architecture), which is seen as the best technology for internal and external interfaces, resulting cost reductions associated with its deployment; combined with standardized protocols, and increased interoperability among IT infrastructures. Studies shows that this flexible architecture will encourage …

Semantic Web Technologies, Dukagjin Hyseni

UBT International Conference

This study attempts to highlight the great importance of developing Semantic Web as one of the best discovery of better data management and presentation within the WWW. Since the W3C's was discovered, initially providing classic web content as web 1.0 that had link / hyperlink of document`s location, then web 2.0 as web-applications have more advanced technologies to connect data, and finally semantic web as extension of web 3.0 also known as Linked Data. The results show that in addition to the rapid development of the Semantic Web, the demand to use its features by data publishers and data readers …

International Conference On Computer Science And Communication Engineering, University For Business And Technology - Ubt

UBT International Conference

UBT Annual International Conference is the 8th international interdisciplinary peer reviewed conference which publishes works of the scientists as well as practitioners in the area where UBT is active in Education, Research and Development. The UBT aims to implement an integrated strategy to establish itself as an internationally competitive, research-intensive university, committed to the transfer of knowledge and the provision of a world-class education to the most talented students from all background. The main perspective of the conference is to connect the scientists and practitioners from different disciplines in the same place and make them be aware of the recent …

A Communication-Centric Framework For Post-Silicon System-On-Chip Integration Debug, Yuting Cao

USF Tampa Graduate Theses and Dissertations

System-on-Chip (SoC) plays an important role in people’s everyday life. These systems are often deployed in critical applications, bugs discovered after their deployment in field can be extremely expensive, resulting in catastrophic loss of company revenues, compromise of personal and national security, and even human life. Post-silicon debug is a critical component of the validation of modern microprocessors and SoC designs. A major challenge in post-silicon debug is the severely limited observability where only a small number of debug interface signals are available to observe a vast space of internal executions of SoC designs. This dissertation addresses the above issues …

Uncovering And Characterizing Splice Variants Associated With Survival In Lung Cancer Patients, Sean West, Sushil Kumar, Surinder K. Batra, Hesham Ali, Dario Ghersi

Interdisciplinary Informatics Faculty Publications

Splice variants have been shown to play an important role in tumor initiation and progression and can serve as novel cancer biomarkers. However, the clinical importance of individual splice variants and the mechanisms by which they can perturb cellular functions are still poorly understood. To address these issues, we developed an efficient and robust computational method to: (1) identify splice variants that are associated with patient survival in a statistically significant manner; and (2) predict rewired protein-protein interactions that may result from altered patterns of expression of such variants. We applied our method to the lung adenocarcinoma dataset from TCGA …

Authentication Usability Methodology, Jean-Baptiste Subils

USF Tampa Graduate Theses and Dissertations

Nowadays many systems require end users to authenticate themselves. Authentication is one of the security activities that end users perform the most. Thus, the usability of this security feature plays a major role in the proper utilization and adoption of a novel authentication method.

This dissertation presents coauthentication, a novel authentication system. Many authentication methods and protocols exist, but passwords remain the predominant authentication method used. Coauthentication is presented here in detail in several possible variations and their associated protocols, with performance comparisons.

This dissertation also presents a framework to evaluate authentication methods in terms of usability.

A large body …

A Gpu-Based Framework For Parallel Spatial Indexing And Query Processing, Zhila Nouri Lewis

USF Tampa Graduate Theses and Dissertations

Support for efficient spatial data storage and retrieval have become a vital component in almost all spatial database systems. Previous work has shown the importance of using spatial indexing and parallel computing to speed up such tasks. While GPUs have become a mainstream platform for high-throughput data processing in recent years, exploiting the massively parallel processing power of GPUs is non-trivial. Current approaches that parallelize one query at a time have low work efficiency and cannot make good use of GPU resources. On the other hand, many spatial database applications are busy systems in which a large number of queries …

Multimodal Emotion Recognition Using 3d Facial Landmarks, Action Units, And Physiological Data, Diego Fabiano

USF Tampa Graduate Theses and Dissertations

To fully understand the complexities of human emotion, the integration of multiple physical features from different modalities can be advantageous. Considering this, this thesis presents an approach to emotion recognition using handcrafted features that consist of 3D facial data, action units, and physiological data. Each modality independently, as well as the combination of each for recognizing human emotion were analyzed.

This analysis includes the use of principal component analysis to determine which dimensions of the feature vector are most important for emotion recognition. The proposed features are shown to be able to be used to accurately recognize emotion and that …

Court Record In The Age Of Artificial Intelligence, Fredric I. Lederer

Popular Media

No abstract provided.

How Do Spinal Surgeons Perceive The Impact Of Factors Used In Post-Surgical Complication Risk Scores?, Enea Parimbelli, Szymon Wilk, Dympna O'Sullivan, Stephen Kingwell, Wojtek Michalowski, Martin Michalowski

Conference papers

When deciding about surgical treatment options, an important aspect of the decision-making process is the potential risk of complications. A risk assessment performed by a spinal surgeon is based on their knowledge of the best available evidence and on their own clinical experience. The objective of this work is to demonstrate the differences in the way spine surgeons perceive the importance of attributes used to calculate risk of post-operative and quantify the differences by building individual formal models of risk perceptions. We employ a preference-learning method - ROR-UTADIS - to build surgeon-specific additive value functions for risk of complications. Comparing …