Computer Sciences Commons^™

Curriculum Development In Technical Education For Boys And Girls Club, Damanpreet Singh

Masters Projects

Technical education has been and will continue to be more and more important to succeed in the future. The Boys and Girls Club, founded in 1860, is a national organization of local chapters which provide voluntary after-school programs for young individuals. The Boys and Girls Club have life-changing programs that prepare the young individuals in the club for their future whether it’s for college, career, or life. The perfect way to prepare best prepare these kids for the future is to develop their technical education. Unfortunately, the boys and girls club of Muskegon has a lack of educational resources for …

Malware Detection And Analysis, Namratha Suraneni

Masters Projects

Malicious software poses a serious threat to the cybersecurity of network infrastructures and is a global pandemic in the form of computer viruses, Trojan horses, and Internet worms. Studies imply that the effects of malware are deteriorating. The main defense against malware is malware detectors. The methods that such a detector employ define its level of quality. Therefore, it is crucial that we research malware detection methods and comprehend their advantages and disadvantages. Attackers are creating malware that is polymorphic and metamorphic and has the capacity to modify their source code as they spread. Furthermore, existing defenses, which often utilize …

Notebooks Web Application, Vivekananda Marellali

Masters Projects

In our day-to-day activities we often need to make quick short notes related to our work, study, or other activities. Later, those notes should be easy to access, modify, delete, share with others, or create PDF documents as and when required. It is ideal if the note content is rich text format such as HTML, as it provides many text formatting options and provide better view and readability. The Notes are better organized if they are grouped into notebooks where each notebook consists of related topic note pages and multiple users can create such notebooks and share with other users …

College Job Portal, Harikrishna Gonuguntla

Masters Projects

Through this project, I am producing a portal called "College Job Portal" that will make life easier for students, colleges, and the companies who hire the students by handling the hiring process. On-campus job placements are a crucial component in contemporary educational institutions. By entering information about their educational history, grades, technological abilities, and CV, students would register with the portal. Like students, companies would sign up with the site by supplying basic details like their address and contact information for human resources. The college would be the portal's administrator. Companies can advertise job openings using this site by including …

Full-Text Search Using Elasticsearch, Akash Shrestha

Masters Projects

Search engines have changed the way we use the internet. They can search or filter out relevant and valuable content of interest to the users. But many of the applications we use today lack search or are just poor. So how can we leverage the same power of search engines in our applications? This project aims to look at “Full-Text Search” which allows us to do a text-based search in text-intensive data. The search will be performed by matching any, or all words of the query exactly or with some relevancy against the indexes created by the searching tool. The …

Cloud Container Security’ Next Move, Vishakha Sadhwani

Dissertations and Theses

In the last few years, it is apparent to cybersecurity experts everywhere that the proverbial container tech genie is out of the bottle, and has been widely embraced across multiple organizations. To achieve the flexibility of building and deploying applications anywhere and everywhere, cloud native environments have gained great momentum and made the development lifecycle simpler than ever. However, container environments brings with them a range of cybersecurity issues that includes images, containers, hosts, runtimes, registries, and orchestration platforms, which needs the necessity to focus on investing in securing your container stack.

According to this report[1], released by cloud-native …

Fairness And Privacy In Machine Learning Algorithms, Neha Bhargava

Master of Science in Computer Science Theses

Roughly 2.5 quintillion bytes of data is generated daily in this digital era. Manual processing of such huge amounts of data to extract useful information is nearly impossible but with the widespread use of machine learning algorithms and their ability to process enormous data in a fast, cost-effective, and scalable way has proven to be a preferred choice to glean useful insights and solve business problems in many domains. With this widespread use of machine learning algorithms there has always been concerns about the ethical issues that may arise from the use of this modern technology. While achieving high accuracies, …

Towards A Machine Learning-Based Digital Twin For Non-Invasive Human Bio-Signal Fusion, Izaldein Al-Zyoud, Fedwa Laamarti, Xiaocong Ma, Diana Tobón, Abdulmotaleb Elsaddik

Computer Vision Faculty Publications

Human bio-signal fusion is considered a critical technological solution that needs to be advanced to enable modern and secure digital health and well-being applications in the metaverse. To support such efforts, we propose a new data-driven digital twin (DT) system to fuse three human physiological bio-signals: heart rate (HR), breathing rate (BR), and blood oxygen saturation level (SpO2). To accomplish this goal, we design a computer vision technology based on the non-invasive photoplethysmography (PPG) technique to extract raw time-series bio-signal data from facial video frames. Then, we implement machine learning (ML) technology to model and measure the bio-signals. We accurately …

A Robust Random Forest Prediction Model For Mother-To-Child Hiv Transmission Based On Individual Medical History, Rebecca Chaula

Tanzania Journal of Engineering and Technology (TJET)

Human Immunodeficiency Virus (HIV) continues to be a leading cause of mortality and reduces manpower throughout the world. HIV transmission from mother to child is still a global challenge in health research. According to UNAIDS, in every 7 girls, 6 are found to be newly infected among adolescents whereby 15-24 years are likely to be living with HIV which is the maternal age and likely to transfer to the child. Machine learning methods have been used to predict HIV/AIDS transmission from mother to child but left behind some important considerations including the use of patient-level information and techniques in balancing …

The Use Of Online Social Media Platforms By Tanzania Journalists To Produce And Disseminate Development News, Elisha Magolanga

Tanzania Journal of Engineering and Technology (TJET)

Advancement in Information and Communication Technologies (ICT) are revolutionizing Development Journalism (DJ) into an effective strategy for building competitive economies globally. However, many countries in Africa including Tanzania are slow in tapping potentials of ICT for development journalism. Digital penetration in the form of the Internet and social media are changing the way in which journalists are mobilizing and engaging communities in journalism practises, a key strategy for a competitive digitalised economy. This paper was guided by Development Communication Theory and Diffusion of Innovation Theory to explore the use of online social media by journalists in Tanzania to practice development …

Isolation Of Ddos Attacks And Flash Events In Internet Traffic Using Deep Learning Techniques, Alex Frank Mongi

Tanzania Journal of Engineering and Technology (TJET)

The adoption of network function visualization (NFV) and software defined radio (SDN) has created a tremendous increase in Internet traffic due to flexibility brought in the network layer. An increase in traffic flowing through the network poses a security threat that becomes tricky to detect and hence selects an appropriate mitigation strategy. Under such a scenario occurrence of the distributed denial of service (DDoS) and flash events (FEs) affect the target servers and interrupt services. Isolating the attacks is the first step before selecting an appropriate mitigation technique. However, detecting and isolating the DDoS attacks from FEs when happening simultaneously …

Iot-Based Smart Fishing Gear For Sustainability Of The Tanzania Blue Economy, Abdi Abdalla

Tanzania Journal of Engineering and Technology (TJET)

The fishing industry engages many Tanzanians and is among the leading sectors of Blue Economy in the country. However, fishing practices are small-scale with poor and insufficient number of fishing facilities, hence limiting productivity and efficacy. Studies argue that the low level of technology currently used in the country could possibly be an impeding factor. Specifically, fishers use non interactive gears that cannot instantaneously update status and alert them whenever the gears are ready for collection. In such scenarios, fishers not only waste their time but also scarce resources such as fuel to facilitate trips to and from the fishing …

Investigating The Support For Agility In Developing Government Software Systems: A Case Of Three East African Countries, Leonard Peter Binamungu

Tanzania Journal of Engineering and Technology (TJET)

Agile Software Development Methods support an iterative and incremental way of developing software systems while responding to change by prioritising various aspects at different times. This differs from traditional sequential methods like Waterfall, in which one software development stage has to be completed before starting the next stage. To produce software systems that meet the requirements of their institutions, several governments in Africa have issued standards and guidelines to be followed during the development of government software systems. Such standards and guidelines specify the specific activities and deliverables for each stage of software development. While well-intentioned, such guidelines and standards …

On Blockchain Performance Enhancement: A Systematic Map Of Strategies Used, Anthony Kigombola

Tanzania Journal of Engineering and Technology (TJET)

Blockchain technology is one among the recent innovations in the computing industry. Blockchains have gathered a widespread interest in the industry mainly due to their security promise. Despite the anticipated benefits of Blockchains, there are several limitations which make the technology less suitable in large scale applications such as banking, one being low throughput. Several initiatives to improve the throughput of Blockchains are being tried out both in the academia and the business worlds but no systematic classification of the initiatives and the strategies used has been done. This study explores Blockchain performance improvement initiatives and classify the initiatives by …

On The Use Of Machine Learning For Causal Inference In Extreme Weather Events, Yuzhe Wang

Discovery Undergraduate Interdisciplinary Research Internship

Machine learning has become a helpful tool for analyzing data, and causal Inference is a powerful method in machine learning that can be used to determine the causal relationship in data. In atmospheric and climate science, this technology can also be applied to predicting extreme weather events. One of the causal inference models is Granger causality, which is used in this project. Granger causality is a statistical test for identifying whether one time series is helpful in forecasting the other time series. In granger causality, if a variable X granger-causes Y: it means that by using all information without …

Lawrence County Archives Website, Brianna Hawkins, Areeb Mohammed, David Niederweis, Mary-Kate Rynders

Honors Capstone Projects and Theses

No abstract provided.

Polarmix: A General Data Augmentation Technique For Lidar Point Clouds, Aoran Xiao, Jiaxing Huang, Dayan Guan, Kaiwen Cui, Shijian Lu, Ling Shao

Computer Vision Faculty Publications

LiDAR point clouds, which are usually scanned by rotating LiDAR sensors continuously, capture precise geometry of the surrounding environment and are crucial to many autonomous detection and navigation tasks. Though many 3D deep architectures have been developed, efficient collection and annotation of large amounts of point clouds remain one major challenge in the analytics and understanding of point cloud data. This paper presents PolarMix, a point cloud augmentation technique that is simple and generic but can mitigate the data constraint effectively across different perception tasks and scenarios. PolarMix enriches point cloud distributions and preserves point cloud fidelity via two cross-scan …

Towards Improving Calibration In Object Detection Under Domain Shift, Muhammad Akhtar Munir, Muhammad Haris Khan, M. Saquib Sarfraz, Mohsen Ali

Computer Vision Faculty Publications

With deep neural network based solution more readily being incorporated in real-world applications, it has been pressing requirement that predictions by such models, especially in safety-critical environments, be highly accurate and well-calibrated. Although some techniques addressing DNN calibration have been proposed, they are only limited to visual classification applications and in-domain predictions. Unfortunately, very little to no attention is paid towards addressing calibration of DNN-based visual object detectors, that occupy similar space and importance in many decision making systems as their visual classification counterparts. In this work, we study the calibration of DNN-based object detection models, particularly under domain shift. …

Intermediate Prototype Mining Transformer For Few-Shot Semantic Segmentation, Yuanwei Liu, Nian Liu, Xiwen Yao, Junwei Han

Computer Vision Faculty Publications

Few-shot semantic segmentation aims to segment the target objects in query under the condition of a few annotated support images. Most previous works strive to mine more effective category information from the support to match with the corresponding objects in query. However, they all ignored the category information gap between query and support images. If the objects in them show large intra-class diversity, forcibly migrating the category information from the support to the query is ineffective. To solve this problem, we are the first to introduce an intermediate prototype for mining both deterministic category information from the support and adaptive …

A Call For Research: Ethical Dilemmas Of Autonomous Vehicle Manufacturers, Remy Harwood

Cybersecurity Undergraduate Research Showcase

While autonomous vehicles accounted for about 31.4 million vehicles on the road in 2019 (Placek). They have continued to flood the market and have a projected growth to 58 million in just 8 years from now (Placek) As well as a market cap in the billions of dollars. Even the comparatively new AV company Tesla has over 3 times the market cap value of the leading non AV brand Toyota (Market Cap) who are also working toward AVs as well, like their level 2 teammate driver assistance. Following Moore’s Law, as technology continues to improve, their social impact and ethical …

Investigating Privacy Policies Using Policylint Tool, Tricia Camaya

Cybersecurity Undergraduate Research Showcase

Organizations essentially inform clients about data collection and sharing practices through privacy policies. Recent research has proposed tools to help users better comprehend these lengthy and intricate legal documents that summarize collection and sharing. However, these instruments have a significant flaw. They overlook the possibility of contradictions within a particular policy. This paper introduces PolicyLint, a tool for analyzing privacy policies that simultaneously considers negation and varying semantic levels of data objects and entities. PolicyLint accomplishes this by using sentence-level natural language processing to automatically create ontologies from a large corpus of privacy policies and capturing both positive and negative …

Ethical Concerns In Self-Driving Cars, Victoria Shand

Cybersecurity Undergraduate Research Showcase

Automobiles have been in existence since 1672 and only went up from there. Self-driving cars are a fantastic piece of technology; they can self-park, laser ranger finder, and near vision; they can map the road in advance, understand road signs, and, in some cases, handle certain variables on the road.

When talking about any form of technology, the possibilities are endless technology is a continuously evolving idea. When discussing self-driving cars, they have some fantastic and encouraging benefits and ideas. Some ideas would be that vehicles could communicate with each other, we could eliminate the need for traffic lights, and …

Explainable Ai Helps Bridge The Ai Skills Gap: Evidence From A Large Bank, Selina Carter, Jonathan Hersh

Economics Faculty Articles and Research

Advances in machine learning have created an “AI skills gap” both across and within firms. As AI becomes embedded in firm processes, it is unknown how this will impact the digital divide between workers with and without AI skills. In this paper we ask whether managers trust AI to predict consequential events, what manager characteristics are associated with increasing trust in AI predictions, and whether explainable AI (XAI) affects users’ trust in AI predictions. Partnering with a large bank, we generated AI predictions for whether a loan will be late in its final disbursement. We embedded these predictions into a …

Assessing Wood Failure In Plywood By Deep Learning/Semantic Segmentation, Ramon Ferreira Oliveira

Theses and Dissertations

The current method for estimating wood failure is highly subjective. Various techniques have been proposed to improve the current protocol, but none have succeeded. This research aims to use deep learning/semantic segmentation using SegNet architecture to estimate wood failure in four types of three-ply plywood from mechanical shear strength specimens. We trained and tested our approach on custom and commercial plywood with bio-based and phenol-formaldehyde adhesives. Shear specimens were prepared and tested. Photographs of 255 shear bonded areas were taken. Forty photographs were used to solicit visual estimates from five human evaluators, and the remaining photographs were used to train …

Algorithmic Solutions To Combat Online Fake News, Xinyi Zhou

Dissertations - ALL

The unprecedented growth of new information producing, distributing, and consuming every moment on the Web has fostered the rise of ``fake news.'' Because of its detrimental effect on democracy, global economies, and public health, effectively combating online fake news has become an essential and urgent task.

This dissertation starts with making typological, theoretical, and empirical efforts to promote the public's comprehension of fake news and lay the foundation for algorithmically combating fake news. As there has been no universal definition of fake news, this dissertation discusses the definition of fake news from three dimensions: veracity, intention, and news, comparing it …

Augmented Reality Fonts With Enhanced Out-Of-Focus Text Legibility, Mohammed Safayet Arefin

Theses and Dissertations

In augmented reality, information is often distributed between real and virtual contexts, and often appears at different distances from the viewer. This raises the issues of (1) context switching, when attention is switched between real and virtual contexts, (2) focal distance switching, when the eye accommodates to see information in sharp focus at a new distance, and (3) transient focal blur, when information is seen out of focus, during the time interval of focal distance switching. This dissertation research has quantified the impact of context switching, focal distance switching, and transient focal blur on human performance and eye fatigue in …

Examining The Relationship Between Stomiiform Fish Morphology And Their Ecological Traits, Mikayla L. Twiss

All HCAS Student Capstones, Theses, and Dissertations

Trait-based ecology characterizes individuals’ functional attributes to better understand and predict their interactions with other species and their environments. Utilizing morphological traits to describe functional groups has helped group species with similar ecological niches that are not necessarily taxonomically related. Within the deep-pelagic fishes, the Order Stomiiformes exhibits high morphological and species diversity, and many species undertake diel vertical migration (DVM). While the morphology and behavior of stomiiform fishes have been extensively studied and described through taxonomic assessments, the connection between their form and function regarding their DVM types, morphotypes, and daytime depth distributions is not well known. Here, three …

Iitd At The Wanlp 2022 Shared Task: Multilingual Multi-Granularity Network For Propaganda Detection, Shubham Mittal, Preslav Nakov

Natural Language Processing Faculty Publications

We present our system for the two subtasks of the shared task on propaganda detection in Arabic, part of WANLP'2022. Subtask 1 is a multi-label classification problem to find the propaganda techniques used in a given tweet. Our system for this task uses XLM-R to predict probabilities for the target tweet to use each of the techniques. In addition to finding the techniques, Subtask 2 further asks to identify the textual span for each instance of each technique that is present in the tweet; the task can be modeled as a sequence tagging problem. We use a multi-granularity network with …

Transfer Of Personality Through Text Style, Michael O'Mahony, Robert Ross

Other resources

The style of generated text is how something is said rather than what is said. We hypothesize that changing the style of generated text can change the perceived personality of the text generation agent. Dialogue systems that aim to imitate a human agent can appear to have a consistent personality through a consistent, controllable style of conversation. Some recent work on the style of generated text [1] performs impressively in the small number of domains selected for their experiments using transformer and LSTM-based models. Lin et al. [1] used weak supervised learning as their data set lacks parallel data. The …

A Maturity Model Of Data Modeling In Self-Service Business Intelligence Software, Anna Kurenkov

Master of Science in Information Technology Theses

Although Self-Service Business Intelligence (SSBI) is continually being adopted in various industries, there is a lack of research focused on data modeling in SSBI. This research aims to fill that research gap and propose a maturity model for SSBI data modeling which is generalizeable between different software and applicable for users of all technical backgrounds. Through extensive literature review, a five-tier maturity model was proposed, explained, and instantiated in PowerBI and Tableau. The testing of the model was found to be simple and intuitive, and the research concludes that the model is applicable to enterprise SSBI environments. This research is …