Computer Sciences Commons^™

Selective Personalization And Group Profiles For Improved Web Search Personalization, Samira Karimi Mansoub, Gönenç Ercan, İlyas Çi̇çekli̇

Turkish Journal of Electrical Engineering and Computer Sciences

Personalization is a common technique used in Web search engines to improve the effectiveness of retrieval. While personalizing some queries yields significant improvements in user experience by providing a ranking in line with the user preferences, it fails to improve or even degrades the effectiveness for less ambiguous queries. A potential personalization metric could improve search engines by selectively applying personalization. One such measure, click entropy uses the query history and the clicked documents for the query, which might be sparse for some queries. In this article, the topic entropy measure is improved by integrating the user distribution into the …

An Alternative Method Of Biomedical Signal Transmission Through The Gsm Voice Channel, Seyedmohsen Dehghan, Mehmet Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

In this work, a new solution for online and accurate biomedical data transmission is presented. For this purpose, a global system for mobile (GSM) communication voice channel is, for the first time, used as a communication link between the patient and healthcare provider. Biomedical signals are converted into speech-like signals before being transferred over a GSM voice channel. On the receiver side, speech-like symbols are stored in a symbols bank, and constructed using random stochastic signals. On the receiver end, the index of the symbol with the most similarity to the received signal is selected as the identified sample. This …

Wavelength Sensitivity Of Indium Tin Oxide On Surface Plasmon Resonance Angles, Antonio Ruiz, Carlos Villa Angulo, Ivan Olaf Hernandez-Fuentes

Turkish Journal of Electrical Engineering and Computer Sciences

Surface plasmon resonance (SPR) is a charge-density oscillation that occurs when a beam of p-polarized monochromatic light impinges with a greater angle than the critical angle in a dielectric-metal interface. Because of the high losses related to metals, the generated surface plasmon waves propagate with high attenuation in the visible and near-infrared spectral regions in most of the dielectric-metal interfaces. An alternative to reduce such losses is to use a transparent indium tin oxide (ITO) film. In this paper, we compared theoretical calculations and experimental measurements of the SPR angle $\theta_{SPR}$ on the interfaces of a borosilicate prism (Bp) and …

Where Did The Time Go?, John C. Viaud, Bilal Abdulmajid, Vitali Surmach, Jia Yanxia

Capstone Showcase

Study shows that most people spend a full quarter of their active hours on their mobile device which can take a serious toll on our productivity as well as our mental and physical well-being. We created an Android app that is able to track and visualize phone usage patterns to help user establish awareness of how much and in what ways they use their Android devices. Unlike currently existing phone time management apps, such as Apple’s ScreenTime and Google’s new Digital Wellbeing, our app provides functionalities to encourage off-phone time and personal goal management.

Transfer Equivalency Site For The Registrar, Janelle N. Rohrbach, Alissa C. Cielecki, Jules A. Turner

Capstone Showcase

The website, arcadia-transfer-equiv.com, was drafted and created for Bill Enick, Registrar at Arcadia University. This was an expansion of a preliminary version of the website created by Caleigh Diefenthaler, Christian Charney, and Dylan Power. The site includes two transfer equivalency tools which can be used to search for course equivalencies by academic institution or by a given Arcadia course. The tools, which pull from a database maintained by the Registrar, will display courses that have transferred to the University successfully. The website also hosts two interactive forms. These forms allow Arcadia students to request approval for courses that have or …

Modeling Gene Expression With Differential Equations, Madison Kuduk

Capstone Showcase

Gene expression is the process by which the information stored in DNA is convertedinto a functional gene product, such as protein. The two main functions that makeup the process of gene expression are transcription and translation. Transcriptionand translation are controlled by the number of mRNA and protein in the cell. Geneexpression can be represented as a system of first order differential equations for the rateof change of mRNA and proteins. These equations involve transcription, translation,degradation and feedback loops. In this paper, I investigate a system of first orderdifferential equations to model gene expression proposed by Hunt, Laplace, Miller andPham in …

Exploration And Implementation Of Neural Ordinary Differential Equations, Long Huu Nguyen, Andy Malinsky

Capstone Showcase

Neural ordinary differential equations (ODEs) have recently emerged as a novel ap- proach to deep learning, leveraging the knowledge of two previously separate domains, neural networks and differential equations. In this paper, we first examine the back- ground and lay the foundation for traditional artificial neural networks. We then present neural ODEs from a rigorous mathematical perspective, and explore their advantages and trade-offs compared to traditional neural nets.

Complex Ciliary Flows Around Stentor Polymorphus In Solutions Of 2% Buttermilk And Chlamydomonas Reinhardtii, Eliana B. Smithstein

Scripps Senior Theses

Stentor are large, unicellular ciliates of the Heterotricha order. They live in both freshwater and marine habitats and are mostly found in ponds. I studied Stentor polymorphus, which is a species of Stentor only recently discovered to be lab culturable. They range from 0.5-1.5mm in length and are unusual because they live with endosymbiotic algae and are much more likely than other, more widely studied, species of Stentor to form aggregates while they are eating. There are three main components to this thesis: First, I established protocols for keeping a viable S. polymorphus culture, since no protocols had been …

Recurrent Neural Network Properties And Their Verification With Monte Carlo Techniques, Dmitry Vengertsev, Elena Sherman

Computer Science Faculty Publications and Presentations

As RNNs find its applications in medical and automotive fields, they became a part of critical systems, which traditionally require thorough verification processes. In this work we present how RNNs behaviors can be modeled as labeled transition systems and formally define a set of state and temporal safety properties for such models. To verify those properties we propose to use the Monte Carlo approach and evaluate its effectiveness for different type of properties. We perform empirical evaluation on two RNN models to determine to what extent they satisfy the properties and how many the samples of Monte Carlo required to …

What Snippets Feel: Depression, Search, And Snippets, Ashlee Milton, Maria Soledad Pera

Computer Science Faculty Publications and Presentations

Mental health disorders (MHD) is a rising, yet stigmatized, topic in the United States. Individuals suffering from MHD are slowing starting to overcome this stigma by discussing how technology affects them. Researchers have explored behavioral nuances that emerge from interactions of individuals affected by MHD with persuasive technologies, mainly social media. Yet, there is a gap in the analysis pertaining to search engines, another persuasive technology, which is part of their everyday lives. In this paper, we report the results of an initial exploratory analysis conducted to understand the sentiment/emotion profiles of search engines handling the information needs of searchers …

Say It With Emojis: Co-Designing Relevance Cues For Searching In The Classroom, Mohammad Aliannejadi, Monica Landoni, Theo Huibers, Emiliana Murgia, Maria Soledad Pera

Computer Science Faculty Publications and Presentations

Search Engine Result Pages (SERP) include snippets of retrieved resources as a means to help searchers select the ones that satisfy their information needs. This way, result relevance can be determined by scanning through snippets, an exercise that requires experience with reading, understanding, and assessing the value of a document. These are skills that primary school children are still developing and thus are not yet proficient with. As web search tools are essential to support children learning at school and home, we explore how to help young searchers in making informed relevance assessments while conducting searches in a classroom. In …

Prediction Of Fatality Crashes With Multilayer Perceptron Of Crash Record Information System Datasets, Thanh Hung Duong, Fengxiang Qiao, Jyh-Haw Yeh, Yunpeng Zhang

Computer Science Faculty Publications and Presentations

Despite the effort of the authorities and researchers, there has been no sign of decreasing in the number of fatal crashes annually. To analyze the deadly collisions, researchers have focused on finding which factors affect injury severity, and thus many crash prediction models for it had been developed. Commonly the injury severity is categorized into five different classes. Still, in many studies, minority classes like fatality and incapacitating injury were merged so that the dataset becomes balanced, and the model can provide decent predictions. However, this approach does not help analyze the fatal crashes as they are joined with other …

On Using Model For Downstream Responsibility, Frances S. Grodzinsky, Marty J. Wolf, Keith W. Miller

School of Computer Science & Engineering Faculty Publications

The authors identify features of software and the software development process that may contribute to the differences in the level of responsibility assigned to the software developers when they make their software available for others to use as a tool in building a second piece of software. They call this second use of the software "downstream use."

Zhvillimi I Time Attendance Sistemit Të Bazuar Në Arduino, Mërgim Alidema

Theses and Dissertations

Procesi i përcjellës së kohës se kur është filluar puna dhe kohëzgjatjes së saj ka qenë një çështje e komplikuar. Për shumë vite shumë metoda janë zhvilluar për të monitoruar prezencën e punëtoreve në vendin e tyre të punës. Më të popullarizuarat kanë qenë karta kohore dhe pasqyra e mungesave.

Secila nga këto opsione ka disavantazhët e veta. Në dekadën e fundit shumë kompani kanë filluar të integrojnë softuerin dhe pajisje moderne për regjistrimin e hyrje-daljeve që të monitorojnë prezencën e punëtoreve të tyre. Këto sistem përveç që ofrojnë regjistrimin e hyrje-daljeve janë në gjendje edhe të gjenerojnë raporte ditore, …

Needfinding, Devorah Kletenik

Open Educational Resources

This activity guides students through the process needfinding to identify areas of need for their creation of a technology for the "public good." Students will conduct contextual inquiry to identify the needs of their target audience.

Personas, Scenarios And Storyboards, Devorah Kletenik

Open Educational Resources

This activity guides students towards the creation of personas, scenarios and storyboards for a product/website that they are creating.

Public Interest Technology: Coding For The Public Good, Devorah Kletenik

Open Educational Resources

These slides are used to guide a discussion with students introducing them to the notion of public interest technology and coding for the public good. The lesson is intended to spark a discussion with students about different sorts of technology and their societal ramifications.

Accessibility: The Whys And The Hows, Devorah Kletenik

Open Educational Resources

This presentation introduces Computer Science students to the notion of accessibility: developing software for people with disabilities. This lesson provides a discussion of why accessibility is important (including the legal, societal and ethical benefits) as well as an overview of different types of impairments (visual, auditory, motor, neurological/cognitive) and how developers can make their software accessible to users with those disabilities. This lesson includes videos and links to readings and tutorials for students.

Coding For The Public Good: Front-End Website Design And Development, Devorah Kletenik

Open Educational Resources

This activity helps student design and develop a front-end of a website, from wireframes through HTML/CSS/Javascript. It includes design questions for students, including the invocation of Ben Schneiderman's eight golden rules for interface design.

Note: this activity assumes prior knowledge of web development. Since this activity is designed for an HCI course, with a focus on interface design, students are not expected to create a back-end for it. This activity can obviously be modified for a full-stack experience.

Accessibility Evaluation, Devorah Kletenik

Open Educational Resources

This activity guides students through the evaluation of a website that they have created to see if it is accessible for users with disabilities. Students will simulate a number of different disabilities (e.g. visual impairments, color blindness, auditory impairments, motor impairments) to see if their website is accessible; they will also use automated W3 and WAVE tools to evaluate their sites. Students will consider the needs of users with disabilities by creating a persona and scenario of a user with disabilities interacting with their site. Finally, students will write up recommendations to change their site and implement the changes.

Structural And Lexical Methods For Auditing Biomedical Terminologies, Rashmie Abeysinghe

Theses and Dissertations--Computer Science

Biomedical terminologies serve as knowledge sources for a wide variety of biomedical applications including information extraction and retrieval, data integration and management, and decision support. Quality issues of biomedical terminologies, if not addressed, could affect all downstream applications that use them as knowledge sources. Therefore, Terminology Quality Assurance (TQA) has become an integral part of the terminology management lifecycle. However, identification of potential quality issues is challenging due to the ever-growing size and complexity of biomedical terminologies. It is time-consuming and labor-intensive to manually audit them and hence, automated TQA methods are highly desirable. In this dissertation, systematic and scalable …

Estimating Free-Flow Speed With Lidar And Overhead Imagery, Armin Hadzic

Theses and Dissertations--Computer Science

Understanding free-flow speed is fundamental to transportation engineering in order to improve traffic flow, control, and planning. The free-flow speed of a road segment is the average speed of automobiles unaffected by traffic congestion or delay. Collecting speed data across a state is both expensive and time consuming. Some approaches have been presented to estimate speed using geometric road features for certain types of roads in limited environments. However, estimating speed at state scale for varying landscapes, environments, and road qualities has been relegated to manual engineering and expensive sensor networks. This thesis proposes an automated approach for estimating free-flow …

Deep Neural Architectures For End-To-End Relation Extraction, Tung Tran

Theses and Dissertations--Computer Science

The rapid pace of scientific and technological advancements has led to a meteoric growth in knowledge, as evidenced by a sharp increase in the number of scholarly publications in recent years. PubMed, for example, archives more than 30 million biomedical articles across various domains and covers a wide range of topics including medicine, pharmacy, biology, and healthcare. Social media and digital journalism have similarly experienced their own accelerated growth in the age of big data. Hence, there is a compelling need for ways to organize and distill the vast, fragmented body of information (often unstructured in the form of natural …

Temporal Data Extraction And Query System For Epilepsy Signal Analysis, Yan Huang

Theses and Dissertations--Computer Science

The 2016 Epilepsy Innovation Institute (Ei2) community survey reported that unpredictability is the most challenging aspect of seizure management. Effective and precise detection, prediction, and localization of epileptic seizures is a fundamental computational challenge. Utilizing epilepsy data from multiple epilepsy monitoring units can enhance the quantity and diversity of datasets, which can lead to more robust epilepsy data analysis tools. The contributions of this dissertation are two-fold. One is the implementation of a temporal query for epilepsy data; the other is the machine learning approach for seizure detection, seizure prediction, and seizure localization. The three key components of our temporal …

Image Instance Segmentation: Using The Cirsy System To Identify Small Objects In Low Resolution Images, Orghomisan William Omatsone

Dissertations

The CIRSY system (or Chick Instance Recognition System) is am image processing system developed as part of this research to detect images of chicks in highly-populated images that uses the leading algorithm in instance segmentation tasks, called the Mask R-CNN. It extends on the Faster R-CNN framework used in object detection tasks, and this extension adds a branch to predict the mask of an object along with the bounding box prediction. Mask R-CNN has proven to be effective ininstance segmentation and object de-tection tasks after outperforming all existing models on evaluation of the Microsoft Common Objects in Context (MS COCO) …

Machine Learning Assisted Gait Analysis For The Determination Of Handedness In Able-Bodied People, Hugh Gallagher

Dissertations

This study has investigated the potential application of machine learning for video analysis, with a view to creating a system which can determine a person’s hand laterality (handedness) from the way that they walk (their gait). To this end, the convolutional neural network model VGG16 underwent transfer learning in order to classify videos under two ‘activities’: “walking left-handed” and “walking right-handed”. This saw varying degrees of success across five transfer learning trained models: Everything – the entire dataset; FiftyFifty – the dataset with enough right-handed samples removed to produce a set with parity between activities; Female – only the female …

An Examination Of The Smote And Other Smote-Based Techniques That Use Synthetic Data To Oversample The Minority Class In The Context Of Credit-Card Fraud Classification, Eduardo Parkinson De Castro

Dissertations

This research project seeks to investigate some of the different sampling techniques that generate and use synthetic data to oversample the minority class as a means of handling the imbalanced distribution between non-fraudulent (majority class) and fraudulent (minority class) classes in a credit-card fraud dataset. The purpose of the research project is to assess the effectiveness of these techniques in the context of fraud detection which is a highly imbalanced and cost-sensitive dataset. Machine learning tasks that require learning from datasets that are highly unbalanced have difficulty learning since many of the traditional learning algorithms are not designed to cope …

Transformer Neural Networks For Automated Story Generation, Kemal Araz

Dissertations

Towards the last two-decade Artificial Intelligence (AI) proved its use on tasks such as image recognition, natural language processing, automated driving. As discussed in the Moore’s law the computational power increased rapidly over the few decades (Moore, 1965) and made it possible to use the techniques which were computationally expensive. These techniques include Deep Learning (DL) changed the field of AI and outperformed other models in a lot of fields some of which mentioned above. However, in natural language generation especially for creative tasks that needs the artificial intelligent models to have not only a precise understanding of the given …

Identifying Online Sexual Predators Using Support Vector Machine, Yifan Li

Dissertations

A two-stage classification model is built in the research for online sexual predator identification. The first stage identifies the suspicious conversations that have predator participants. The second stage identifies the predators in suspicious conversations. Support vector machines are used with word and character n-grams, combined with behavioural features of the authors to train the final classifier. The unbalanced dataset is downsampled to test the performance of re-balancing an unbalanced dataset. An age group classification model is also constructed to test the feasibility of extracting the age profile of the authors, which can be used as features for classifier training. The …

Classification Of Animal Sound Using Convolutional Neural Network, Neha Singh

Dissertations

Recently, labeling of acoustic events has emerged as an active topic covering a wide range of applications. High-level semantic inference can be conducted based on main audioeffects to facilitate various content-based applications for analysis, efficient recovery and content management. This paper proposes a flexible Convolutional neural network-based framework for animal audio classification. The work takes inspiration from various deep neural network developed for multimedia classification recently. The model is driven by the ideology of identifying the animal sound in the audio file by forcing the network to pay attention to core audio effect present in the audio to generate Mel-spectrogram. …