Computer Sciences Commons^™

Infusing Raspberry Pi In The Computer Science Curriculum For Enhanced Learning, Fitratullah Khan, Mahmoud K. Quweider, Ala Qubbaj, Emmett Tomai, Lei Xu, Liyu Zhang, Hansheng Lei

Computer Science Faculty Publications

With the advent of cloud computing, the Internet of Things (IoT), and mobile computing, CS faculty are continuously revamping the curriculum material to address such burgeoning set of technologies in practical and relatable ways. Raspberry Pi (RPi) devices represent an ideal hardware/software framework that embodies all these technologies through its simple architecture, small form factor (that minimizes the volume and footprint of a desktop computer), and ability to integrate various sensors that network together and connect to the Cloud. Therefore, one of the strategies of Computer Science Department, to enhance depth of learning concepts, has been to infuse Raspberry Pi …

Translating Counting Problems Into Computable Language Expressions, Zach Prescott

Theses

The realm of automated problem solving is a relatively new field, even in the context of natural language processing. One area where this is often demonstrated is that of creating a program that can solve word problems. The program must understand the problem, perform some processing, and then convey this information to a user in a way that is accessible and understandable. There has been quite a lot of progress in this area with simpler problems. However, when it comes to understanding problems that involve a level of NLP, the results are not conclusive. In this paper, we would like …

Sentiment Analysis In Peer Review, Zachariah J. Beasley

USF Tampa Graduate Theses and Dissertations

Sentiment analysis, a widely popular subfield of natural language processing, has recently been used in the classroom to predict student attrition or to determine the mood of students, teacher strengths and weaknesses, or student perception of internship experience. These are all helpful indicators for the enhancement of students' academic experience but none improve the information gathered from or the reliability of peer review. This is particularly important in large courses with complex assignments (e.g., essays, software projects, and presentations) where scalable grading is requisite. In this dissertation, we apply sentiment analysis not on an assignment itself, but on the meaningful …

Action Recognition Using The Motion Taxonomy, Maxat Alibayev

USF Tampa Graduate Theses and Dissertations

In the last years, modern action recognition frameworks with deep architectures have achieved impressive results on the large-scale activity datasets. All state-of-the-art models share one common attribute: two-stream architectures. One deep model takes RGB frames, while the other model is fed with pre-computed optical flow vectors. The outputs of both models are combined to be used as a final probability distribution for the action classes. When comparing the results of individual models with the fused model, it is common to see that that latter method is more superior. Researchers explain that phenomena with the fact that optical flow vectors serve …

High Performance Computing Education: Current Challenges And Future Directions, Rajendra K. Raj, Carol J. Romanowski, John Impagliazzo, Sherif G. Aly, Brett A. Becker, Juan Chen, Sheikh Ghafoor, Nasser Giacaman, Steven I. Gordon, Cruz Izu, Shahram Rahimi, Michael P. Robson, Neena Thota

Computer Science: Faculty Publications

High Performance Computing (HPC) is the ability to process data and perform complex calculations at extremely high speeds. Current HPC platforms can achieve calculations on the order of quadrillions of calculations per second, with quintillions on the horizon. The past three decades witnessed a vast increase in the use of HPC across different scientific, engineering, and business communities on problems such as sequencing the genome, predicting climate changes, designing modern aerodynamics, or establishing customer preferences. Although HPC has been well incorporated into science curricula such as bioinformatics, the same cannot be said for most computing programs. Computing educators are only …

Literature Review: How U.S. Government Documents Are Addressing The Increasing National Security Implications Of Artificial Intelligence, Bert Chapman

Libraries Faculty and Staff Scholarship and Research

This article emphasizes the increasing importance of artificial intelligence (AI) in military and national security policy making. It seeks to inform interested individuals about the proliferation of publicly accessible U.S. government and military literature on this multifaceted topic. An additional objective of this endeavor is encouraging greater public awareness of and participation in emerging public policy debate on AI's moral and national security implications..

Investigation Of Enhanced Double Weight Code In Point To Point Access Networks, Hesham A. Bakarman, Ali Z. Ghazi Zahid, M. H. Mezher, Al Aboud Wahed Al-Isawi, Feras N. Hasoon, Saad H. Al-Isawi, Hussein A. Rasool, Sahbudin Shaari, Maitham Al-Alyawy, S. T. Yousif, Jaber K. Taher, Ali H. Mezher, Hala Musawy, W. Y. Chong, R. Zakaria

Research outputs 2014 to 2021

© 2020 Published under licence by IOP Publishing Ltd. In this paper, an investigation and evaluation to enhanced double weight (EDW) code is performed, a new technique for code structuring and building using modified arithmetical model has been given for the code in place of employing previous technique based on Trial Inspections. Innovative design has been employed for the code into P2P networks using diverse weighted EDW code to be fitting into optical CDMA relevance applications. A new developed relation for EDW code is presented, the relation is based on studying and experimenting the effect of input transmission power with …

An Assessment Of Global Research Activities On Children And Adolescent Online Security, Adeola O. Opesade Dr, Omolayo A. Adesina Ms.

Journal of Cybersecurity Education, Research and Practice

The use of the Internet among children and adolescents is now a norm in many parts of the world. As the Internet offers a wide range of benefits to these ones, so does it expose them to possible various risks and harm. Researchers in different countries across the world have engaged in the production of relevant research-based knowledge in order to make the virtual world a safe place for the younger ones. However, while studies have been carried out on the subject of Internet risk among children and adolescents, there is a dearth of information on the assessment of research …

Evaluating And Securing Text-Based Java Code Through Static Code Analysis, Jeong Yang, Young Lee, Amanda Fernandez, Joshua Sanchez

Journal of Cybersecurity Education, Research and Practice

As the cyber security landscape dynamically evolves and security professionals work to keep apace, modern-day educators face the issue of equipping a new generation for this dynamic landscape. With cyber-attacks and vulnerabilities substantially increased over the past years in frequency and severity, it is important to design and build secure software applications from the group up. Therefore, defensive secure coding techniques covering security concepts must be taught from beginning computer science programming courses to exercise building secure applications. Using static analysis, this study thoroughly analyzed Java source code in two textbooks used at a collegiate level, with the goal of …

Malaware Defensive: A Game To Train Users To Combat Malware, Tyler Moon, Tamirat Abegaz, Bryson Payne, Abi Salimi

Journal of Cybersecurity Education, Research and Practice

Several research findings indicate that basic cyber hygiene can potentially deter the majority of cyber threats. One of the ways cybersecurity professionals can prepare users to ensure proper hygiene is to help them develop their ability to spot the difference between normal and abnormal behavior in a computer system. Malware disrupts the normal behavior of a computer system. The lack of appropriate user training has been one of the main reasons behind the exposure of computer systems to threats, from social engineering to viruses, trojans, and ransomware. Basic knowledge about common behavioral characteristics of malware could help users identify potentially …

Toward High Performance Computing Education, Rajendra K. Raj, Carol J. Romanowski, Sherif G. Aly, Brett A. Becker, Juan Chen, Sheikh Ghafoor, Nasser Giacaman, Steven I. Gordon, Cruz Izu, Shahram Rahimi, Michael P. Robson, Neena Thota

Computer Science: Faculty Publications

High Performance Computing (HPC) is the ability to process data and perform complex calculations at extremely high speeds. Current HPC platforms can achieve calculations on the order of quadrillions of calculations per second with quintillions on the horizon. The past three decades witnessed a vast increase in the use of HPC across different scientific, engineering and business communities, for example, sequencing the genome, predicting climate changes, designing modern aerodynamics, or establishing customer preferences. Although HPC has been well incorporated into science curricula such as bioinformatics, the same cannot be said for most computing programs. This working group will explore how …

Iot Privacy And Security: Challenges And Solutions, Lo'ai A. Tawalbeh, Fadi Muheidat, Mais Tawalbeh, Muhannad Quwaider

Computer Science Faculty Publications (Archived)

Privacy and security are among the significant challenges of the Internet of Things (IoT). Improper device updates, lack of efficient and robust security protocols, user unawareness, and famous active device monitoring are among the challenges that IoT is facing. In this work, we are exploring the background of IoT systems and security measures, and identifying (a) different security and privacy issues, (b) approaches used to secure the components of IoT-based environments and systems, (c) existing security solutions, and (d) the best privacy models necessary and suitable for different layers of IoT driven applications. In this work, we proposed a new …

Motifs Enable Communication Efficiency And Fault-Tolerance In Transcriptional Networks, Satyaki Roy, Preetam Ghosh, Dipak Barua, Sajal K. Das

Computer Science Faculty Research & Creative Works

Analysis of the topology of transcriptional regulatory networks (TRNs) is an effective way to study the regulatory interactions between the transcription factors (TFs) and the target genes. TRNs are characterized by the abundance of motifs such as feed forward loops (FFLs), which contribute to their structural and functional properties. In this paper, we focus on the role of motifs (specifically, FFLs) in signal propagation in TRNs and the organization of the TRN topology with FFLs as building blocks. To this end, we classify nodes participating in FFLs (termed motif central nodes) into three distinct roles (namely, roles A, B …

Prototypical Career Paths In Urban, Suburban, And Rural Locations In The United States, Tenace Kwaku Setor, Damien Joseph

Information Systems and Quantitative Analysis Faculty Publications

Career paths are formed over time from interactions between individuals, organizations, and labor markets within and across geographic locations. What are the prototypical career paths thus formed? Who are the likely incumbents of these career paths? What are the consequences of pursuing these career paths? This study combines micro-level perspectives on personal agency and macro-level institutional factors to explain how careers unfold over time and space. The juxtaposition of micro- and macro-level factors contributes to career research and practice, which have traditionally examined careers as movements across organizations and occupations over time, but almost exclusively within specific geographic locations. We …

Towards Ryser's Conjecture: Bounds On The Cardinality Of Partitioned Intersecting Hypergraphs, Anna E. Dodson

Dartmouth College Undergraduate Theses

This work is motivated by the open conjecture concerning the size of a minimum vertex cover in a partitioned hypergraph. In an r-uniform r-partite hypergraph, the size of the minimum vertex cover C is conjectured to be related to the size of its maximum matching M by the relation (|C|<= (r-1)|M|). In fact it is not known whether this conjecture holds when |M| = 1. We consider r-partite hypergraphs with maximal matching size |M| = 1, and pose a novel algorithmic approach to finding a vertex cover of size (r - 1) in this case. We define a reactive hypergraph to be a back-and-forth algorithm for a hypergraph which chooses new edges in response to a choice of vertex cover, and prove that this algorithm terminates for all hypergraphs of orders r = 3 and 4. We introduce the idea of optimizing the size of the reactive hypergraph and find that the reactive hypergraph terminates for r = 5...20. We then consider the case where the intersection of any two edges is exactly 1. We prove bounds on the size of this 1-intersecting hypergraph and relate the 1-intersecting hypergraph maximization problem to mutually orthogonal Latin squares. We propose a generative algorithm for 1-intersecting hypergraphs of maximal size for prime powers r-1 = pd under the constraint pd+1 is also a prime power of the same form, and therefore pose a new generating algorithm for MOLS based upon intersecting hypergraphs. We prove this algorithm generates a valid set of mutually orthogonal Latin squares and prove the construction guarantees certain symmetric properties. We conclude that a conjecture by Lovasz, that the inequality in Ryser's Conjecture cannot be improved when (r-1) is a prime power, is correct for the 1-intersecting hypergraph of prime power orders.

Visual Feature Extraction From Dermoscopic Colour Images For Classification Of Melanocytic Skin Lesions, Walid Al-Zyoud, Athar Abu Helou, Eslam Alqasem, Nathir A. Rawashdeh

Michigan Tech Publications, Part 1

The early diagnosis of Melanoma is a challenging task for dermatologists, because of the characteristic similarities of Melanoma with other skin lesions such as typical moles and dysplastic nevi. Aims: This work aims to help both experienced and non-experienced dermatologists in the early detection of cutaneous Melanoma through the development of a computational helping tool based on the “ABCD” rule of dermoscopy. Moreover, it aims to decrease the need for invasive biopsy procedure for each tested abnormal skin lesion. Methods: This is accomplished through the utilization of MATLAB programming language to build a feature extraction tool for the assessment of …

Denial Of Service Attack Detection Through Machine Learning For The Iot, Naeem Firdous Syed, Zubair Baig, Ahmed Ibrahim, Craig Valli

Research outputs 2014 to 2021

Sustained Internet of Things (IoT) deployment and functioning are heavily reliant on the use of effective data communication protocols. In the IoT landscape, the publish/subscribe-based Message Queuing Telemetry Transport (MQTT) protocol is popular. Cyber security threats against the MQTT protocol are anticipated to increase at par with its increasing use by IoT manufacturers. In particular, IoT is vulnerable to protocol-based Application layer Denial of Service (DoS) attacks, which have been known to cause widespread service disruption in legacy systems. In this paper, we propose an Application layer DoS attack detection framework for the MQTT protocol and test the scheme on …

What’S In The Cloud? - An Examination Of The Impact Of Cloud Storage Usage On The Browser Cache., Graeme Horsman

Journal of Digital Forensics, Security and Law

Cloud storage is now a well established and popular service adopted by many individuals, often at limited or no cost. It provides users with the ability to store content on a cloud service provider’s infrastructure offering the benefit of redundancy, reliability, security, flexibility of access and the potential assumed liability of the provider for data loss within the contexts of a licensing agreement. Consequently, this form of remote storage provides a regulatory challenge as content which once resided upon a seized digital exhibit, available for scrutiny during a digital forensic investigatory, may no longer be present where attempting to acquire …

An Evaluation Of Data Erasing Tools, Andrew Jones, Isaac Afrifa

Journal of Digital Forensics, Security and Law

The permanent removal of data from media is a major area of concern mainly because of the misconception that once a file is deleted or storage media is formatted, it cannot be recovered. There has been the development of both commercial and freeware data erasing tools, which all claim complete file or disk erasure. This report analyzes the efficiency of a number of these tools in performing erasures on an electromechanical drive. It focuses on a selection of popular and modern erasing tools; taking into consideration their usability, claimed erasing standards and whether they perform complete data erasure with the …

Automating The Classification Of Mosquito Specimens Using Image Processing Techniques, Mona Minakshi

USF Tampa Graduate Theses and Dissertations

According to WHO (World Health Organization) reports, among all animals, mosquitoes are responsible for the most deaths worldwide. Mosquito borne diseases continue to pose grave dangers to global health. In 2015 alone, 214 million cases of malaria were registered worldwide. According to Centers for Disease Control and Prevention (CDC) report published in 2016, 62,500 suspected case of Zika were reported to the Puerto Rico Department of Health (PRDH) out of which 29,345 cases were found positive. The year 2019 was recorded as the worst for dengue in South East Asia. There are close to 4,500 species of mosquitoes (spread across …

Android Application For Agv, Gurpreet Singh Sudan

Manipal Institute of Technology, Manipal Theses and Dissertations

No abstract provided.

Method Of Local Splins Of Modeling Signals Measured At Unequal Intervals, Rahimjon K. Azimov, Madaminjon K. Mahkamov, Bunyod R. Azimov

Scientific Bulletin. Physical and Mathematical Research

This article is devoted to the construction of spline models for signals measured at unequal intervals. Cubic spline models built at unequal intervals have a high accuracy of signal interpolation, which allows professionals to make informed decisions as a result of digital signal processing. As an example, a cubic spline interpolation model was constructed for digital processing of geophysical signals measured at unequal intervals. Geophysical signals are very important to us, because the ever-growing demand for natural resources around the world requires ever-increasing oil and gas production. This, in its turn, requires a more consistent and extensive exploration of oil …

Finite-Difference Method For Calculating A Gas Pipeline Laid Over Rough Terrain, Madaminjon K. Mahkamov, Orifjon Sh. Bozorov, Ismatulla K. Khujaev

Scientific Bulletin. Physical and Mathematical Research

A numerical method is proposed for solving the problem of pipeline transportation of natural gas through a non-horizontal gas pipeline, when the law of change in the hydrostatic pressure in time is specified at the inlet of the section, and the law of change in the mass flow of gas is set at the output.

The nonlinear, quasi-one-dimensional equations of pipeline gas transport in the isothermal approach are transformed using the natural logarithm of dimensionless gas density and the introduction of forward and backward traveling waves. In the newly constructed system of equations, convective and resistance forces are nonlinear, and …

Modeling Multi-Targets Sentiment Classification Via Graph Convolutional Networks And Auxiliary Relation, Ao Feng, Zhengjie Gao, Xinyu Song, Ke Ke, Tianhao Xu, Xuelei Zhang

All Faculty Scholarship for the College of the Sciences

Existing solutions do not work well when multi-targets coexist in a sentence. The reason is that the existing solution is usually to separate multiple targets and process them separately. If the original sentence has N target, the original sentence will be repeated for N times, and only one target will be processed each time. To some extent, this approach degenerates the fine-grained sentiment classification task into the sentencelevel sentiment classification task, and the research method of processing the target separately ignores the internal relation and interaction between the targets. Based on the above considerations, we proposes to use Graph Convolutional …

Cup-Net: Compressed Ultrafast Photography Using Convolutional Neural Networks, Matthew Parker

ENGS 88 Honors Thesis (AB Students)

Compressed ultrafast photography (CUP) is a cutting-edge imaging technique that uses a variation of the traditional streak camera to obtain video at 100 billion frames per second with a single exposure. In order to achieve this level of temporal detail, CUP leverages compressed sensing (CS). Compressed sensing theory states that a compressed representation of an image can be directly acquired using a non-adaptive measurement matrix so long as the encoding matrix follows certain properties such as restrictive isometry and incoherence. This compressed representation of the original scene can later be reconstructed back into the original form. CUP applies CS by …

Pathways To The Native Storyteller: A Method To Enable Computational Story Understanding, Aramide O. Kehinde

College of Computing and Digital Media Dissertations

The primary objective of this thesis is to develop a method that uses machine learning algorithms to enable computational story understanding. This research is conducted with the aim of establishing a system called the Native Storyteller that plans and creates storytelling experiences for human users. The paper first establishes the desired capabilities of the system and then deep dives into how to enable story understanding, which is the core ability the system needs to function. As such, the research places emphasis on natural language processing and its application to solving key problems in this context. Namely, machine representation of story …

Perfect Recovery (2,N) Color Visual Cryptography Scheme, Xianhuan Zhang, Zhengxin Fu, Ouyang Dan, Bin Yu

Journal of System Simulation

Abstract: Based on XOR operation and combining the characteristic of computer display technology, a perfect recovery (2,n) color visual cryptography scheme was proposed. Sharing algorithm of color secret image was designed on the basis of constructing row vectors${{V}_{1}},{{V}_{2}},\cdots ,{{V}_{n}}$. Through computing shares by XOR operation and dealing with recovery image, the secret image was recovered. The experimental results show that the scheme on the basis of keeping the simplicity in the reconstruction phase of visual cryptography can realize the secret image perfect recovery with low pixel expansion for price. Each participant only needs to carry a share …

Privacy-Preserving And Functional Information Systems, Thang Hoang

USF Tampa Graduate Theses and Dissertations

Information systems generally involve storage and analytics of large-scale data, many of which may be highly sensitive (e.g., personal information, medical records). It is vital to ensure that these systems not only provide essential functionalities at large scale efficiently but also achieve a high level of security against cyber threats. However, there are significant research challenges in offering security and privacy for such information systems while preserving their original functionalities (e.g., search, analytics) effectively. Hence, there is a critical need for efficient cryptographic protocols that can address data privacy vs. utilization dilemma for real-life applications.

In this dissertation, we introduce …

Optimization Sensing Slot Under Transmission Collision Of Primary User And Secondary User In Cognitive Radio System, Chen Song, Nae Zheng, Wang Sheng

Journal of System Simulation

Abstract: In the cognitive radio system, that the primary user (PU) has collision with the secondary user (SU) when the secondary user (SU) was detected properly was considered. The queuing theory was introduced and the PU’s appearance pattern was described by M/M/1 model. Considering the length of the transmitting slot, detection probability and transmitting collision, the function of spectrum usage and transmitting time were established based on the PU’s appearance pattern. The existence of the maximum value of spectrum usage in the definition domain of the transmitting time was proved by theoretical derivation in some condition. The simulation results provide …

Online Identification And Simulation Of Multiple Model Based On Minimum Entropy Clustering, Xiaopeng Zhao, Yongchun Zhang

Journal of System Simulation

Abstract: An online identification algorithm for multiple model based on minimum entropy clustering was investigated. The number of local models and corresponding weights was calculated by the entropy based fuzzy subtractive clustering approach, and the regularity degree of the local system was considered along with the clustering process. Parameters of local models could be estimated online by the weighted recursive least square method. The waste heat recovery Organic Rankine Cycles system was used to demonstrate the algorithm. The result shows the identified multi-model not only can reach an accuracy and reliability identification result, but also has a stronger self-adaptability …