Digital Commons Network^™

Winona State University Improving Our World Blog: 2013-2022, Winona State University

Winona State University Blogs

The Winona State University (WSU) Improving Our World Blog articles and entries from September 2013-February 2022. Note: there may be format coding in the document.

Intelligent Millimeter-Wave System For Human Activity Monitoring For Telemedicine, Abdullah K. Alhazmi, Mubarak A. Alanazi, Awwad H. Alshehry, Saleh M. Alshahry, Jennifer Jaszek, Cameron Djukic, Anna Brown, Kurt Jackson, Vamsy P. Chodavarapu

Electrical and Computer Engineering Faculty Publications

Telemedicine has the potential to improve access and delivery of healthcare to diverse and aging populations. Recent advances in technology allow for remote monitoring of physiological measures such as heart rate, oxygen saturation, blood glucose, and blood pressure. However, the ability to accurately detect falls and monitor physical activity remotely without invading privacy or remembering to wear a costly device remains an ongoing concern. Our proposed system utilizes a millimeter-wave (mmwave) radar sensor (IWR6843ISK-ODS) connected to an NVIDIA Jetson Nano board for continuous monitoring of human activity. We developed a PointNet neural network for real-time human activity monitoring that can …

Gerontovis: Data Visualization At The Confluence Of Aging, Zack While, R. Jordan Crouser, Ali Sarvghad

Computer Science: Faculty Publications

Despite the explosive growth of the aging population worldwide, older adults have been largely overlooked by visualization research. This paper is a critical reflection on the underrepresentation of older adults in visualization research. We discuss why investigating visualization at the intersection of aging matters, why older adults may have been omitted from sample populations in visualization research, how aging may affect visualization use, and how this differs from traditional accessibility research. To encourage further discussion and novel scholarship in this area, we introduce GerontoVis, a term which encapsulates research and practice of data visualization design that primarily focuses on older …

Grammatical Error Correction In Thai Sentences For Deaf Students, Supachan Traitruengsakul

Chulalongkorn University Theses and Dissertations (Chula ETD)

Deaf students encounter challenges in written communication due to errors such as insertion, deletion, disorder, misusage, and misspellings. Grammatical error correction (GEC) technology can help mitigate these issues. However, existing GEC models are primarily trained on online resources from second-language hearing learners. In contrast, sentences written by deaf students suffer from a variety of errors not typically found elsewhere. To address this issue, we create the Thai Deaf Corpus (TDC), focusing on identifying and analyzing errors among deaf students in grades 7-12 across four deaf schools. Additionally, we introduce a two-stage system for the Thai-GEC model, automatically detecting and correcting …

Mhair: A Dataset Of Audio-Image Representations For Multimodal Human Actions, Muhammad Bilal Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar

Research outputs 2022 to 2026

Audio-image representations for a multimodal human action (MHAiR) dataset contains six different image representations of the audio signals that capture the temporal dynamics of the actions in a very compact and informative way. The dataset was extracted from the audio recordings which were captured from an existing video dataset, i.e., UCF101. Each data sample captured a duration of approximately 10 s long, and the overall dataset was split into 4893 training samples and 1944 testing samples. The resulting feature sequences were then converted into images, which can be used for human action recognition and other related tasks. These images can …

Decision Support System For Major Selection In Higher Education For Multimedia Graduate Students Using Fuzzy Mamdani Logic, Khasna Nur Fauziah, Fatchul Arifin

Elinvo (Electronics, Informatics, and Vocational Education)

Students at the vocational high school level are indeed prepared to be able to work directly, but it does not rule out the possibility that vocational high school students can continue higher education such as universities. But the problem that will be faced again if students who graduate from vocational high schools choose to continue their education in college is what major they will take. One of the vocational high school majors, namely Multimedia, has a wide scope, so grade 3 vocational high school students who want to go to college have a dilemma in deciding on a major. This …

An Exhaustive Review Of Neutrosophic Logic In Addressing Image Processing Issues, Samia Mandour

Neutrosophic Systems with Applications

Since the importance of images in our lives and the advancements in computer data gathering methods, anyone can collect a large number of images, but most of them cannot be processed manually. Image processing therefore becomes appealing since various types of data may be represented and processed digitally. Image processing has become the most popular processing method, employed in security camera films, healthcare images, images from remote sensors, and naturalistic image/videos because of fast computers and processors. In order to raise cognitive function and speed up decision-making, image processing is crucial to many information access systems. Since ambiguity now permeates …

The How And Why Of Visual Practice At Un Climate Negotiations, Stéphanie Heckman

New England Journal of Public Policy

In this article Stéphanie Heckman examines the process and outcomes of her graphic recording work and other forms of visual practice in the context of UN climate negotiations, reflecting on three years of collaboration with the UN Climate Change Secretariat, particularly during the eighteen-month Global Stocktake process. After a review of the history and science behind visual storytelling, she analyses one of the graphic recordings made for the third meeting of the Technical Dialogue of the Global Stocktake through the lens of Kelvy Bird’s ‘Levels of Scribing’ model. Drawing on comments from delegates at COP27 in Sharm el-Sheikh, Egypt and …

Cfa-Treated Mice Induce Hyperalgesia In Healthy Mice Via An Olfactory Mechanism, Yangmiao Zhang, Wentai Luo, Maryt M. Heinricher, Andrey E. Ryabinin

Chemistry Faculty Publications and Presentations

Background

Social interactions with subjects experiencing pain can increase nociceptive sensitivity in observers, even without direct physical contact. In previous experiments, extended indirect exposure to soiled bedding from mice with alcohol withdrawal-related hyperalgesia enhanced nociception in their conspecifics. This finding suggested that olfactory cues could be sufficient for nociceptive hypersensitivity in otherwise untreated animals (also known as “bystanders”).

Aim

The current study addressed this possibility using an inflammation-based hyperalgesia model and long- and short-term exposure paradigms in C57BL/6J mice.

Materials & Method

Adult male and female mice received intraplantar injection of complete Freund's adjuvant (CFA) and were used as stimulus …

3-Dimensional Quartic Bézier Curve Approximation Model By Using Neutrosophic Approach, Siti Nur Idara Rosli, Mohammad Izat Emir Zulkifly

Neutrosophic Systems with Applications

In a 3-dimensional data collection process, there exists noise data that cannot be included to visualize the process. Therefore, it is difficult to deal with since fuzzy set and intuitionistic fuzzy set theories did not consider the indeterminacy problem. However, using a neutrosophic approach with three memberships: truth, false, and indeterminacy membership function, the error data will be treated as uncertain data by using the indeterminacy degree. Thus, this study will visualize the 3-dimensional quartic Bézier curve model by using neutrosophic set theory. To construct the model, the neutrosophic quartic control point must first be introduced to approximate the neutrosophic …

Focal Modulation Network For Lung Segmentation In Chest X-Ray Images, Şaban Öztürk, Tolga Çukur

Turkish Journal of Electrical Engineering and Computer Sciences

Segmentation of lung regions is of key importance for the automatic analysis of Chest X-Ray (CXR) images, which have a vital role in the detection of various pulmonary diseases. Precise identification of lung regions is the basic prerequisite for disease diagnosis and treatment planning. However, achieving precise lung segmentation poses significant challenges due to factors such as variations in anatomical shape and size, the presence of strong edges at the rib cage and clavicle, and overlapping anatomical structures resulting from diverse diseases. Although commonly considered as the de-facto standard in medical image segmentation, the convolutional UNet architecture and its variants …

Understanding Stakeholder Experiences With Visual Communication In Environmental Impact Assessment, Ana R. De Oliveira, Sofia Bento, Maria Partidário, Angus Morrison-Saunders

Research outputs 2022 to 2026

Visual communication is widely and commonly used in environmental impact assessment (EIA) practice by all stakeholders. It includes maps, photographs, tables, info-graphics and other images used in environmental impact statements, as well as videos and graphics in online materials or in face-to-face consultation sessions (e.g., posters and PowerPoint presentations). The purpose of this research was to understand the practice of visual communication in EIA, focusing upon the perceptions and experiences of stakeholders. Surveys were conducted with international EIA practitioners along with observations of consultation sessions for three EIA projects in Portugal and interviews with proponents, regulators and members of the …

Dynamic Deep Neural Network Inference Via Adaptive Channel Skipping, Meixia Zou, Xiuwen Li, Jinzheng Fang, Hong Wen, Weiwei Fang

Turkish Journal of Electrical Engineering and Computer Sciences

Deep neural networks have recently made remarkable achievements in computer vision applications. However, the high computational requirements needed to achieve accurate inference results can be a significant barrier to deploying DNNs on resource-constrained computing devices, such as those found in the Internet-of-things. In this work, we propose a fresh approach called adaptive channel skipping (ACS) that prioritizes the identification of the most suitable channels for skipping and implements an efficient skipping mechanism during inference. We begin with the development of a new gating network model, ACS-GN, which employs fine-grained channel-wise skipping to enable input-dependent inference and achieve a desirable balance …

Pymaivar: An Open-Source Python Suit For Audio-Image Representation In Human Action Recognition, Muhammad B. Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar

Research outputs 2022 to 2026

We present PyMAiVAR, a versatile toolbox that encompasses the generation of image representations for audio data including Wave plots, Spectral Centroids, Spectral Roll Offs, Mel Frequency Cepstral Coefficients (MFCC), MFCC Feature Scaling, and Chromagrams. This wide-ranging toolkit generates rich audio-image representations, playing a pivotal role in reshaping human action recognition. By fully exploiting audio data's latent potential, PyMAiVAR stands as a significant advancement in the field. The package is implemented in Python and can be used across different operating systems.

Visualizing Transaction-Level Modeling Simulations Of Deep Neural Networks, Nataniel Farzan, Emad Arasteh

Engineering Technical Reports

The growing complexity of data-intensive software demands constant innovation in computer hardware design. Performance is a critical factor in rapidly evolving applications such as artificial intelligence (AI). Transaction-level modeling (TLM) is a valuable technique used to represent hardware and software behavior in a simulated environment. However, extracting actionable insights from TLM simulations is not a trivial task. We present Netmemvisual, an interactive, cross-platform visualization tool for exposing memory bottlenecks in TLM simulations. We demonstrate how Netmemvisual helps system designers rapidly analyze complex TLM simulations to find memory contention. We describe the project’s current features, experimental results with two state-of-the-art deep …

Generative And Implicit Methods For 3d Point Cloud Processing, Mohammad Samiul Arshad

Computer Science and Engineering Dissertations - Archive

3D point clouds are a popular form of data representation with many applications in computer vision, computer graphics, and robotics. As the output of range sensing devices, point clouds have gained popularity with the current interest in self-driving vehicles. More formally, point clouds are an unordered set of irregular points collected from the surface of an object. Each point consists of a Cartesian coordinate, along with additional information such as an RGB color value and surface normal estimate. However, deep learning methods fall short in the processing of 3D point clouds due to the irregular and permutation-invariant nature of the …

Visualizing Oceanographic Data To Depict Long-Term Changes In Phytoplankton, Patricia S. Thibodeau, Jongsun Kim

School of Earth, Environmental, & Marine Sciences Faculty Publications

Oceanographic time series provide an important perspective on environmental processes in ecosystems. The Narragansett Bay Long-Term Plankton Time Series (NBPTS) in Narragansett Bay, Rhode Island, USA, represents one of the longest plankton time series (1959-present) of its kind in the world and presents a unique opportunity to visualize long-term change within an aquatic ecosystem. Phytoplankton represent the base of the food web in most marine systems, including Narragansett Bay. Therefore, communicating their importance to the 2.4 billion people who live within the coastal ocean is critical. We developed a protocol with the goal of visualizing the diversity and magnitude of …

Towards Improving The Efficacy Of Windows Security Notifier For Apps From Unknown Publishers: The Role Of Rhetoric, Ankit Shrestha, Rizu Paudel, Prakriti Dumaru, Mahdi Nasrullah Al-Ameen

Computer Science Student Research

With over 1.4 billion users of Windows 10, it is the most widely used operating system in the world. In Windows, applications from unknown publishers are popular due to mass availability and ease of access. Installing such applications can lead to malware infection, including viruses and ransomware. Therefore, we explored the design of interventions to prevent the users from installing applications from unknown publishers. To this end, we conducted a lab study with nine participants to understand the perceptions and behavior of users toward the designed interventions. Then, we conducted an online study with 256 participants to evaluate the impact …

Research On Legal Text Matching Based On Pre-Training Model, Chuanming Yu, Yifan Jiang

Journal of Scientific Information Research

[Purpose/significance]This study aims to solve the problem of traditional short text matching models being difficult to apply to long text matching tasks such as legal case retrieval. [Method/process]For the task of legal case matching, this paper proposes a Legal Text Matching model based on RoFormer （LTMR）. In the coding layer, the legal case is encoded through the RoFormer model and the legal feature extractor. In the reasoning layer, the context and interactive information of long text are further extracted by using interactive attention and self-attention mechanisms. We conducted the empirical research by applying the proposed model to the CAIL2019-SCM dataset. …

Inter-Frame Video Compression Based On Adaptive Fuzzy Inference System Compression Of Multiple Frame Characteristics, Arief Bramanto Wicaksono Putra, Rheo Malani, Bedi Suprapty, Achmad Fanany Onnilita Gaffar, Roman Voliansky

Knowledge Engineering and Data Science

Video compression is used for storage or bandwidth efficiency in clip video information. Video compression involves encoders and decoders. Video compression uses intra-frame, inter-frame, and block-based methods. Video compression compresses nearby frame pairs into one compressed frame using inter-frame compression. This study defines odd and even neighboring frame pairings. Motion estimation, compensation, and frame difference underpin video compression methods. In this study, adaptive FIS (Fuzzy Inference System) compresses and decompresses each odd-even frame pair. First, adaptive FIS trained on all feature pairings of each odd-even frame pair. Video compression-decompression uses the taught adaptive FIS as a codec. The features utilized …

Security Of Text To Image Conversions, Zobaida Alssadi

Theses and Dissertations

The use of images and icons to represent news or narratives has grown in popularity. Still, one critical problem is that they are not equivalent to language, making them vulnerable to adversary attacks. This study examines the impact of image-poisoning attacks based on polysemantic words and of image attacks based on cultural differences when converting text to images. Such attacks can lead to the loss of important information and create confusion and incorrect interpretations of the intended meaning, misinforming the general public. The study specifically focuses on possible effects in a news and story context. This study highlights the significance …

Climate Of A Cave Laboratory Representative For Rock Art Caves In The Vézère Area (South-West France), Delphine Lacanette, Léna Bassel, Fabien Salmon, Jean-Christophe Portais, Bruno Bousquet, Rémy Chapoulie, Faten Ammari, Philippe Malaurent, Catherine Ferrier

International Journal of Speleology

Leye Cave (Dordogne, France) is a laboratory cave in the Vézère area, a region that contains some of the most famous rock art caves in the world such as Lascaux, Font-de-Gaume and Combarelles, and is listed as Human World Heritage by UNESCO. Leye Cave was selected because it is representative of painted caves, with respect to parameters such as its geological stage, the presence of water and carbon dioxide, the geological state of its walls, and the size of the cave. These wall states are studied to better understand the conditions of conservation of rock art caves without damaging them. …

Chicken Keypoint Estimation, Rohit Kala

Computer Science and Computer Engineering Undergraduate Honors Theses

Poultry is an important food source across the world. To facilitate the growth of the global population, we must also improve methods to oversee poultry with new and emerging technologies to improve the efficiency of poultry farms as well as the welfare of the birds. The technology we explore is Deep Learning methods and Computer Vision to help automate chicken monitoring using technologies such as Mask R-CNN to detect the posture of the chicken from an RGB camera. We use Meta Research's Detectron 2 to implement the Mask R-CNN model to train on our dataset created on videos of chickens …

Understanding The Role Of Images On Stack Overflow, Dong Wang, Tao Xiao, Christoph Treude, Raula Kula, Hideaki Hata, Yasutaka Kamei

Research Collection School Of Computing and Information Systems

Images are increasingly being shared by software developers in diverse channels including question-and-answer forums like Stack Overflow. Although prior work has pointed out that these images are meaningful and provide complementary information compared to their associated text, how images are used to support questions is empirically unknown. To address this knowledge gap, in this paper we specifically conduct an empirical study to investigate (I) the characteristics of images, (II) the extent to which images are used in different question types, and (III) the role of images on receiving answers. Our results first show that user interface is the most common …

Structure Of Extremal Unit Distance Graphs, Kaylee Weatherspoon

Senior Theses

This thesis begins with a selective overview of problems in geometric graph theory, a rapidly evolving subfield of discrete mathematics. We then narrow our focus to the study of unit-distance graphs, Euclidean coloring problems, rigidity theory and the interplay among these topics. After expounding on the limitations we face when attempting to characterize finite, separable edge-maximal unit-distance graphs, we engage an interesting Diophantine problem arising in this endeavor. Finally, we present a novel subclass of finite, separable edge-maximal unit distance graphs obtained as part of the author's undergraduate research experience.

Application Of The Recitation Method To Improve The Competence Of Medical Laboratory Technology Students In The Immunology Field, Patricia Gita Naully, Perdina Nursidika

Jurnal Pendidikan Sains

An accredited mid-level MLT (Medical Laboratory Technology) must have the competence to perform medical laboratory examinations from pre-analytic, analytic, and post-analytic stages in several fields, one of which is immunology. Many D3 MLT students are facing obstacles to passed the immunology course. This obstacle is not only experienced by students of D3 MLT but also by medical students, pharmacy students, and similar majors. The purpose of this research is to determine the effect of recitation method in the form of animation video making and immunology based device on the competence of Diploma 3 (D3) MLT students. This research is a …

Motif Mining: Finding And Summarizing Remixed Image Content, William Theisen, Daniel Gonzalez Cedre, Zachariah Carmichael, Daniel Moreira, Tim Weninger, Walter Scheirer

Computer Science: Faculty Publications and Other Works

On the Internet, images are no longer static; they have become dynamic content. Thanks to the availability of smartphones with cameras and easy-to-use editing software, images can be remixed (i.e., redacted, edited, and re-combined with other content) on-the-fly, allowing a world-wide audience to repeat the process many times. From digital art to memes, the evolution of images through time is now an important topic of study for digital humanists, social scientists, and media forensics specialists. However, because typical data sets in computer vision are composed of static content, there has been limited development of automated algorithms for analyzing remixed content. …

Effective Strategies For Using Telecommuting By Owners Of Small Businesses, Thomas Law

Walden Dissertations and Doctoral Studies

Small business owners who lack effective strategies to incorporate telecommuting may be unable to retain teleworking employees, create a flexible working environment, or improve workforce morale, negatively impacting company productivity and profitability. Grounded in transformational leadership theory and sociotechnical systems theory, the purpose of this qualitative multiple case study was to explore strategies small business owners use to incorporate telecommuting to retain teleworking employees. Data were collected from five small business owners in Texas with at least 1 year of management experience and created and maintained remote working strategies. Data collection included semistructured interviews and company documents. Three themes emerged …

An Adaptive Image Restoration Algorithm Based On Hybrid Total Variation Regularization, Cong Thang Pham, Thi Thu Thao Tran, Hung Vi Dang, Hoai Phuong Dang

Turkish Journal of Electrical Engineering and Computer Sciences

In imaging systems, the mixed Poisson-Gaussian noise (MPGN) model can accurately describe the noise present. Total variation (TV) regularization-based methods have been widely utilized for Poisson-Gaussian removal with edge-preserving. However, TV regularization sometimes causes staircase artifacts with piecewise constants. To overcome this issue, we propose a new model in which the regularization term is represented by a combination of total variation and high-order total variation. We study the existence and uniqueness of the minimizer for the considered model. Numerically, the minimization problem can be efficiently solved by the alternating minimization method. Furthermore, we give rigorous convergence analyses of our algorithm. …

Video Sign Language Recognition Using Pose Extraction And Deep Learning Models, Shayla Luong

Master's Projects

Sign language recognition (SLR) has long been a studied subject and research field within the Computer Vision domain. Appearance-based and pose-based approaches are two ways to tackle SLR tasks. Various models from traditional to current state-of-the-art including HOG-based features, Convolutional Neural Network, Recurrent Neural Network, Transformer, and Graph Convolutional Network have been utilized to tackle the area of SLR. While classifying alphabet letters in sign language has shown high accuracy rates, recognizing words presents its set of difficulties including the large vocabulary size, the subtleties in body motions and hand orientations, and regional dialects and variations. The emergence of deep …