Computer Sciences Commons^™

Classifier Performance Evaluation For Lightweight Ids Using Fog Computing In Iot Security, Belal Sudqi Khater, Ainuddin Wahid Abdul Wahab, Mohd Yamaniidna Idris, Mohammed Abdulla Hussain, Ashraf Ahmed Ibrahim, Mohammad Arif Amin, Hisham A. Shehadeh

All Works

In this article, a Host-Based Intrusion Detection System (HIDS) using a Modified Vector Space Representation (MVSR) N-gram and Multilayer Perceptron (MLP) model for securing the Internet of Things (IoT), based on lightweight techniques and using Fog Computing devices, is proposed. The Australian Defence Force Academy Linux Dataset (ADFA-LD), which contains exploits and attacks on various applications, is employed for the analysis. The proposed method is divided into the feature extraction stage, the feature selection stage, and classification modeling. To maintain the lightweight criteria, the feature extraction stage considers a combination of 1-gram and 2-gram for the system call encoding. In …

Diagnostic Accuracy Of Machine Learning Models To Identify Congenital Heart Disease: A Meta-Analysis, Zahra Hoodbhoy, Uswa Jiwani, Saima Sattar, Rehana A. Salam, Babar Hasan, Jai K. Das

Department of Paediatrics and Child Health

Background: With the dearth of trained care providers to diagnose congenital heart disease (CHD) and a surge in machine learning (ML) models, this review aims to estimate the diagnostic accuracy of such models for detecting CHD.
Methods: A comprehensive literature search in the PubMed, CINAHL, Wiley Cochrane Library, and Web of Science databases was performed. Studies that reported the diagnostic ability of ML for the detection of CHD compared to the reference standard were included. Risk of bias assessment was performed using Quality Assessment for Diagnostic Accuracy Studies-2 tool. The sensitivity and specificity results from the studies were used to …

The Incubation Effect Among Students Playing An Educational Game For Physics, May Marie P. Talandron-Felipe, Ma. Mercedes T. Rodrigo

Department of Information Systems & Computer Science Faculty Publications

The incubation effect (IE) is a problem-solving phenomenon composed of three phases: pre-incubation where one fails to solve a problem; incubation, a momentary break where time is spent away from the unsolved problem; and post-incubation where the unsolved problem is revisited and solved. Literature on IE was limited to experiments involving traditional classroom activities. This initial investigation showed evidence of IE instances in a computer-based learning environment. This paper consolidates the studies on IE among students playing an educational game called Physics Playground and presents further analysis to examine the incidence of post-incubation or the revisit to a previously unsolved …

P2v-Rcnn: Point To Voxel Feature Learning For 3d Object Detection From Point Clouds, Jiale Li, Yu Sun, Shujie Luo, Ziqi Zhu, Hang Dai, Andrey S. Krylov, Yong Ding, Ling Shao

Computer Vision Faculty Publications

The most recent 3D object detectors for point clouds rely on the coarse voxel-based representation rather than the accurate point-based representation due to a higher box recall in the voxel-based Region Proposal Network (RPN). However, the detection accuracy is severely restricted by the information loss of pose details in the voxels. Different from considering the point cloud as voxel or point representation only, we propose a point-to-voxel feature learning approach to voxelize the point cloud with both the point-wise semantic and local spatial features, which maintains the voxel-wise features to build the high-recall voxel-based RPN and also provides the accurate …

Caries And Restoration Detection Using Bitewing Film Based On Transfer Learning With Cnns, Yi-Cheng Mao, Tsung-Yi Chen, He-Sheng Jhou, Szu-Yin Lin, Sheng-Yu Liu, Yu-An Chen, Yu-Lin Liu, Chiung-An Chen, Yen-Cheng Huang, Shih-Lun Chen, Chun-Wei Li, Patricia Angela R. Abu, Wei-Yuan Chiang

Department of Information Systems & Computer Science Faculty Publications

Caries is a dental disease caused by bacterial infection. If the cause of the caries is detected early; the treatment will be relatively easy; which in turn prevents caries from spreading. The current common procedure of dentists is to first perform radiographic examination on the patient and mark the lesions manually. However; the work of judging lesions and markings requires professional experience and is very time-consuming and repetitive. Taking advantage of the rapid development of artificial intelligence imaging research and technical methods will help dentists make accurate markings and improve medical treatments. It can also shorten the judgment time of …

Facility Location Games With Ordinal Preferences, Hau Chan, Minming Li, Chenhao Wang

School of Computing: Faculty Publications

We consider a new setting of facility location games with ordinal preferences. In such a setting, we have a set of agents and a set of facilities. Each agent is located on a line and has an ordinal preference over the facilities. Our goal is to design strategyproof mechanisms that elicit truthful information (preferences and/or locations) from the agents and locate the facilities to minimize both maximum and total cost objectives as well as to maximize both minimum and total utility objectives. For the four possible objectives, we consider the 2-facility settings in which only preferences are private, or locations …

Understanding User's Behavior And Protection Strategy Upon Losing, Or Identifying Unauthorized Access To Online Account, Huzeyfe Kocabas, Swapnil Nandy, Tanjina Tamanna, Mahdi Nasrullah Al-Ameen

Computer Science Student Research

A wide-range of personal and sensitive information are stored in users’ online accounts. Losing access, or an unauthorized access to one of those accounts could put them into the risks of privacy breach, cause financial loss, and compromise their accessibility to important information and documents. A large body of prior work focused on developing new schemes and strategies to protect users’ online security. However, there is a dearth in existing literature to understand users’ strategies and contingency plans to protect their online accounts once they lose access, or identify an unauthorized access to one of their accounts. We addressed this …

Understanding User Behavior, Information Exposure, And Privacy Risks In Managing Old Devices, Mahdi Nasrullah Al-Ameen, Tanjina Tamanna, Swapnil Nandy, Huzeyfe Kocabas

Computer Science Student Research

The goal of this study is to understand the behavior of users from developing countries in managing an old device (e.g., computer, mobile phone), which has been replaced by a new device, or suffers from technical issues providing a notion that it may stop working soon. The prior work explored the ecology and challenges of repairing old devices in developing regions. However, it is still understudied how the strategies of people from developing countries in managing their personal information on old devices could impact their digital privacy. To address this gap in existing literature, we conducted semi-structured interview with 52 …

Reshaping The Landscape Of The Future: Software-Defined Manufacturing, Lei Xu, Lin Chen, Zhimin Gao, Hiram Moya, Weidong Shi

Computer Science Faculty Publications

We describe the concept of software-defined manufacturing, which divides the manufacturing ecosystem into software definition and physical manufacturing layers. Software-defined manufacturing allows better resource sharing and collaboration, and it has the potential to transform the existing manufacturing sector.

Design, Deployment, And Validation Of Computer Vision Techniques For Societal Scale Applications, Arup Kanti Dey

USF Tampa Graduate Theses and Dissertations

Artificial Intelligence techniques have ensued a significant impact on our daily lives. Numerous applications in so many diverse fields have been made possible by AI algorithms today, and there are many more yet to come. In this dissertation, we design, deploy and validate computer vision algorithms for innovative and high-impact societal scale applications.We specifically focus on two applications in this dissertation: Detection of distracted driving and Detection of breeding habitats of mosquito vectors.

Distracted driving on roads is a major problem around the world. Distracted driving is the case where a driver diverts his/her focus from the road and engages …

Infinite Peirce Distribution In The Algebra Of Compact Operators And Description Of Its Local Au-Tomorphisms, Farhodjon N. Arzikulov, Rejabboy Qo’Shaqov

Scientific Bulletin. Physical and Mathematical Research

In the present paper the infinite Peirce decomposition of the algebra 𝐾(𝐻) of com-pact operators on an infinite dimensional separable Gilbert space 𝐻 is constructed, using the norm of the algebra 𝐾(𝐻) and a maximal family of mutually or-thogonal minimal projections, i.e., self-adjoint,idempotent elements. The infinite Peirce decompo-sition on the norm of a 𝐶∗-algebra is also con-structed in 2012 by the first author. But, it turns, the condition, applied then, is not sufficient for the infi-nite Peirce decomposition on the norm constructed in 2012 to be an algebra. Therefore, in the present paper, the infinite Peirce decomposition on the norm …

What Is The Uncertainty Of The Result Of Data Processing: Fuzzy Analogue Of The Central Limit Theorem, Julio C. Urenda, Olga Kosheleva, Shahnaz Shahbazova, Vladik Kreinovich

Departmental Technical Reports (CS)

It is known that, due to the Central Limit Theorem, the probability distribution of the uncertainty of the result of data processing is, in general, close to Gaussian -- or to a distribution from a somewhat more general class known as infinitely divisible. We show that a similar result holds in the fuzzy case: namely, the membership function describing the uncertainty of the result of data processing is, in general, close to Gaussian -- or to a membership function from an explicitly described more general class.

Certis: Digital Transformation Of A Physical Security Company, Singapore Management University

Perspectives@SMU

How a company synonymous with auxiliary police injected sensors and artificial intelligence into its 21st century operations

On The Use Of Minimum Penalties In Statistical Learning, Ben Sherwood, Bradley S. Price

Faculty & Staff Scholarship

Modern multivariate machine learning and statistical methodologies estimate parameters of interest while leveraging prior knowledge of the association between outcome variables. The methods that do allow for estimation of relationships do so typically through an error covariance matrix in multivariate regression which does not scale to other types of models. In this article we proposed the MinPEN framework to simultaneously estimate regression coefficients associated with the multivariate regression model and the relationships between outcome variables using mild assumptions. The MinPen framework utilizes a novel penalty based on the minimum function to exploit detected relationships between responses. An iterative algorithm that …

Edge Detail Analysis Of Wear Particles, Mohammad Shakeel Laghari, Ahmed Hassan, Mubashir Noman

Computer Vision Faculty Publications

Tribology is the study of wear particles that are generated in all machines with interacting mechanical parts. Particles are separated from the surfaces due to friction and relative motion. These microscopic particles vary in certain characteristics of size, quantity, composition, and morphology. Wear particles or wear debris are categorized by six morphological attributes of shape, edge details, texture, color, size, and thickness ratio. Particles can be identified with the help of some or all of these attributes however, only edge details analysis is considered in this paper. The objective is to classify these particles in a coherent way based on …

"Negative" Results -- When The Measured Quantity Is Outside The Sensor's Range -- Can Help Data Processing, Jonatan Contreras, Francisco Zapata, Olga Kosheleva, Vladik Kreinovich, Martine Ceberio

Departmental Technical Reports (CS)

In many real-life situations, we know the general form of the dependence y = f(x, c₁, ..., c_m) between physical quantities, but the values need to be determined experimentally, based on the results of measuring x and y. In some cases, we do not get any result of measuring y since the actual value is outside the range of the measuring instrument. Usually, such cases are ignored. In this paper, we show that taking these cases into account can help data processing -- by improving the accuracy of our estimates of c_i and thus, …

So How To Make Group Decisions? Arrow's Impossibility Theorem 70 Years After, Hung T. Nguyen, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In 1951, Kenneth Arrow proved that it is not possible to have a group decision making procedure that satisfies reasonable requirements like fairness. From the theoretical viewpoint, this is a great result -- well-deserving the Nobel Prize that was awarded to Professor Arrow. However, from the practical viewpoint, the question remains -- so how should we make group decisions? A usual way to solve this problem is to provide some reasonable heuristic ideas, but the problem is that different seemingly reasonable idea often lead to different group decision -- this is known, e.g., for different voting schemes. In this paper, …

Knot Theory In Virtual Reality, Donald Lee Price

Masters Theses & Specialist Projects

Throughout the study of Knot Theory, there have been several programmatic solutions to common problems or questions. These solutions have included software to draw knots, software to identify knots, or online databases to look up pre-computed data about knots. We introduce a novel prototype of software used to study knots and links by using Virtual Reality. This software can allow researchers to draw links in 3D, run physics simulations on them, and identify them. This technique has not yet been rigorously explored and we believe it will be of great interest to Knot Theory researchers. The computer code is written …

Examining The Effects Of Race On Human-Ai Cooperation, Akil A. Atkins, Christopher L. Dancy, Matthew S. Brown

Faculty Conference Papers and Presentations

Recent literature has shown that racism and implicit racial biases can affect one’s actions in major ways, from the time it takes police to decide whether they shoot an armed suspect, to a decision on whether to trust a stranger. Given that race is a social/power construct, artifacts can also be racialized, and these racialized agents have also been found to be treated differently based on their perceived race. We explored whether people’s decision to cooperate with an AI agent during a task (a modified version of the Stag hunt task) is affected by the knowledge that the AI agent …

Material Detection With Thermal Imaging And Computer Vision: Potentials And Limitations, Jared Poe

Graduate Theses and Dissertations

The goal of my masters thesis research is to develop an affordable and mobile infraredbased environmental sensoring system for the control of a servo motor based on material identification. While this sensing could be oriented towards different applications, my thesis is particularly interested in material detection due to the wide range of possible applications in mechanical engineering. Material detection using a thermal mobile camera could be used in manufacturing, recycling or autonomous robotics. For my research, the application that will be focused on is using this material detection to control a servo motor by identifying and sending control inputs based …

Computational Frameworks For Multi-Robot Cooperative 3d Printing And Planning, Laxmi Prasad Poudel

Graduate Theses and Dissertations

This dissertation proposes a novel cooperative 3D printing (C3DP) approach for multi-robot additive manufacturing (AM) and presents scheduling and planning strategies that enable multi-robot cooperation in the manufacturing environment. C3DP is the first step towards achieving the overarching goal of swarm manufacturing (SM). SM is a paradigm for distributed manufacturing that envisions networks of micro-factories, each of which employs thousands of mobile robots that can manufacture different products on demand. SM breaks down the complicated supply chain used to deliver a product from a large production facility from one part of the world to another. Instead, it establishes a network …

What Fuzzy And Quantum Computing Can Learn From The Success Of Deep Learning, Shahnaz Shahbazova, Vladik Kreinovich

Departmental Technical Reports (CS)

How can we apply the ideas that made deep neural networks successful to other aspects of computing? For this purpose, we reformulate these ideas in a more general form -- and we show that this generalization also covers fuzzy and quantum computing. This enables us to suggest that similar ideas can be helpful for fuzzy and quantum computing as well. In this suggestion, we are encouraged by the fact that as we show, to some extent, these ideas are already helpful.

Why Quantum Techniques Are A Good First Approximation To Economic Phenomena, And What Next, Vladik Kreinovich, Olga Kosheleva

Departmental Technical Reports (CS)

Somewhat surprisingly, several formulas of quantum physics -- the physics of micro-world -- provide a good first approximation to many social phenomena, in particular, to many economic phenomena, phenomena which are very far from micro-physics. In this paper, we provide three possible explanations for this surprising fact. First, we show that several formulas from quantum physics actually provide a good first-approximation description for many phenomena in general, not only to the phenomena of micro-physics. Second, we show that some quantum formulas represent the fastest way to compute nonlinear dependencies and thus, naturally appear when we look for easily computable models; …

Integrimi I Sistemit Të Menaxhimit Dixhital Të Pasurive Të Patundshme Bazuar Në Arkitekturën E Pastërt Mvc, Mynevere Hyseni

Theses and Dissertations

Integrimi i sistemit të menaxhimit dixhital të pasurive të patundshme është shumë i rëndësishëm për menaxhim të mbarë të pasurive të patundshme dhe pozicionimin e tyre në treg si dhe luan rol të veçantë në sigurimin e avantazhit të një kompanie ose të një individi të vetëm ndaj konkurrentëve. Kur një individ apo kompani dëshiron të shes/jep me qira ndonjë pasuri të vetën, është mjaft e nevojshme që ta prezantojnë atë me botën në mënyrë të zhurmshme. Po ashtu në anën tjetër kur ndonjë individ dëshiron të blej/marr me qira ndonjë pronë kërkon mundësi më të lehtë dhe më të …

Analizë E Testimit Të Aplikacioneve Të Telefonave Mobile, Deliza Muharremaj

Theses and Dissertations

Testimi i aplikacioneve softuerike është një proces i cili shërben për të kontrolluar nëse aplikacioni është pa gabime ose jo. Është proces i verifikimit dhe vlerësimit të shërbimeve softuerike, duke kontrolluar nëse aplikacioni softuerik është duke i plotësuar kërkesat e përdoruesit dhe nëse funksionon sipas karakteristikave. Qëllimi i testimit është të identifikojë gabimet, boshllëqet ose kërkesat që mungojnë në raport me kërkesat aktuale.

Testimi është i rëndësishëm sepse nëse ka ndonjë gabim ai mund të identifikohet herët dhe mund të zgjidhet para dorëzimit përfundimtar të produktit. Testimi i aplikacioneve mobile është një grumbullim i aktiviteteve të lidhuara për gjetjen e …

Zhvillimi I Seo-S Ndër Vite, Berna Zehri

Theses and Dissertations

Duke e pasur parasysh kërkesat e bizneseve që të jenë më të ekspozuara në rrjetet sociale dhe në motorët e kërkimit si Google, thuhet që SEO është thelbësore që të ndihmojë të arrihen shumë nga qëllimet e bizneseve. SEO (Search Engine Optimization) ndihmon të krijohen marrëdhënie më të mira me audiencën, të përmirësohet përvoja e klientit, rrit autoritetin e biznesit, ndihmon në rritjen e klikimeve në faqe, jep përparësi ndaj konkurrencës dhe i rrit konvertimet, që do të thotë më shumë shitje, klientë më besnikë dhe më shumë rritje për bizneset e fushave te ndryshme.

Në këtë punim, analizohet zhvillimi …

Inteligjenca Artificiale (Ai) - Benefitet Dhe Frika Ndaj Së Ardhmës, Ardit Azemi

Theses and Dissertations

Këtë temë diplome e kam përzgjedhur sepse është teknologji relativisht e re, inteligjenca artificiale është e ardhmja e njerëzimit, dhe në një të ardhme të afërt do ju ndihmoj shumë njerëzve duke u lehtuar shumë punë, mirëpo ekziston edhe frika se mos do i zëvendësoj në disa raste të caktuara edhe vet njerëzit, pra punën të cilën ata bëjnë, pa dyshim në disa fusha përkatëse do të ketë ndikim revulucionar.

Pasiqë është një teknologji e cila ka një degëzim shumë të gjerë po thuajse në çdo sferë të jetës dhe po ashtu për shumë kë termi “Inteligjencë Artificiale” është i …

Zhvillimi I Një Ueb Aplikacioni Duke Përdorur Arkitekturën E Mikroserviseve Dhe Kubernetes, Fisnik Zejnullahu

Theses and Dissertations

Në këtë punim diplome do të shqyrtohen mënyrat e ndryshme që përdoren për zhvillimin e aplikacioneve, e sidomos do të shqyrtohen mënyrat dhe teknologjitë moderne që po përdoren dhe që janë të preferueshme të përdoren në ditët e sotme. Lexuesi në fillim do të njoftohet me një hyrje rreth mënyrave dhe teknologjive që përdoren për zhvillimin e aplikacioneve, pastaj do të njoftohet me problemet dhe vështirësitë rreth zhvillimit të aplikacioneve e si mund t’i zgjidhim ato probleme. Do të vazhdohet me shqyrtimin e literaturës për këto teknologji, dhe diskutimi më në detaje rreth tyre. Do të flasim për të mirat …

Insights And Lessons Learned From The Design, Development And Deployment Of Pervasive Location-Based Mobile Systems “In The Wild”, Konstantinos Papangelis, Alan Chamberlain, Nicolas Lalone, Ting Cao

Presentations and other scholarship

This paper, based on a reflective approach, presents several insights and lessons learned from the design, development, and deployment of a location-based social network and a location-based game. These are analyzed and discussed against the life-cycle of our studies and range from engaging with the participants to dealing with technical issues while on the field. Overall, the insights and lessons learned illustrate that one should be prepared and flexible enough to accommodate any issues as they arise in a professional manner considering not only the results of the study but also the participants and the researchers involved.The aim of this …

Self-Supervised Contrastive Learning For Code Retrieval And Summarization Via Semantic-Preserving Transformations, Duy Quoc Nghi Bui, Yijun Yu, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

We propose Corder, a self-supervised contrastive learning framework for source code model. Corder is designed to alleviate the need of labeled data for code retrieval and code summarization tasks. The pre-trained model of Corder can be used in two ways: (1) it can produce vector representation of code which can be applied to code retrieval tasks that do not have labeled data; (2) it can be used in a fine-tuning process for tasks that might still require label data such as code summarization. The key innovation is that we train the source code model by asking it to recognize similar …