Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 25 of 25
Full-Text Articles in Entire DC Network
Speechqoe: A Novel Personalized Qoe Assessment Model For Voice Services Via Speech Sensing, Chaowei Wang, Huadi Zhu, Ming Li
Speechqoe: A Novel Personalized Qoe Assessment Model For Voice Services Via Speech Sensing, Chaowei Wang, Huadi Zhu, Ming Li
Association of Computing Machinery Open Access Agreement Publications
Quality of Experience (QoE) assessment is a long-lasting but yet-tobe-resolved task. Existing approaches, especially for conversational voice services, are restricted to leveraging network-centric parameters. However, their performances are hardly satisfactory due to the failure to consider comprehensive QoE-related factors. Moreover, they develop a one-for-all model that is uniform for all individuals and thus incapable of handling user diversity in QoE perception. This paper proposes a personalized QoE assessment model, namely SpeechQoE. It exploits speaker’s speech signals to infer individual’s perceived quality in voice services. SpeechQoE fundamentally addresses the drawback of conventional models. Instead of enumerating and incorporating unlimited QoE-related factors, …
Poster Abstract: Constory: Automatic Story Investigator Of Public Perception On The Mega Urban Infrastructure Project, Alireza Shamshiri, Rok Ryu Kyeong, Steven Mccullough, June Young Park
Poster Abstract: Constory: Automatic Story Investigator Of Public Perception On The Mega Urban Infrastructure Project, Alireza Shamshiri, Rok Ryu Kyeong, Steven Mccullough, June Young Park
Association of Computing Machinery Open Access Agreement Publications
We evaluate the North Houston Highway Improvement Project (NHHIP) in Texas by analyzing social media data (Twitter) to determine the public perception on a series of issues in the project. We analyze the pertinent tweets since the project announcement (2008 to 2021). Our initial analysis is based on three distinct periods in which the volume of tweets has changed according to notable events: 1) release of the alternative design by the agency and 2) project pause, using topic modeling. Our results show a long-term public opinion shift from project itself to community and demolition. Although ’Neighborhood and Homes’-related tweets were …
Inequity By Inequity: Community Driven Investigation Of Wheelchair User Discomfort By Infrastructure Failures, Steven Mccullough, Jessica Eisma, June Young Park, Mikila Salazar, Sarah F. Rose
Inequity By Inequity: Community Driven Investigation Of Wheelchair User Discomfort By Infrastructure Failures, Steven Mccullough, Jessica Eisma, June Young Park, Mikila Salazar, Sarah F. Rose
Association of Computing Machinery Open Access Agreement Publications
Wheelchair users face a variety of disability-related inequities in the built environment. The primary challenge is that current legislation for relieving disability inequities focuses on design guidelines and less so in monitoring their discomfort. While there is literature about monitoring wheelchair users, there is little available data regarding wheelchair user discomfort across the built environment. Therefore, we create a transformative approach to measure a wheelchair user’s personal comfort (WheelCom) using open-source solutions, allowing more citizens to engage in the inequity challenge. To demonstrate, we lectured our approach to local high school students to develop WheelCom. Subsequently, actual wheelchair users measured …
Psdoodle: Fast App Screen Search Via Partial Screen Doodle, Soumik Mohian, Christoph Csallner
Psdoodle: Fast App Screen Search Via Partial Screen Doodle, Soumik Mohian, Christoph Csallner
Association of Computing Machinery Open Access Agreement Publications
Searching through existing repositories for a specific mobile app screen design is currently either slow or tedious. Such searches are either limited to basic keyword searches (Google Image Search) or require as input a complete query screen image (SWIRE). A promising alternative is interactive partial sketching, which is more structured than keyword search and faster than complete-screen queries. PSDoodle is the first system to allow interactive search of screens via interactive sketching. PSDoodle is built on top of a combination of the Rico repository of some 58k Android app screens, the Google QuickDraw dataset of icon-level doodles, and DoodleUINet, a …
Slnet: A Redistributable Corpus Of 3rd-Party Simulink Models, Sohil Lal Shrestha, Shafiul Azam Chowdhury, Christoph Csallner
Slnet: A Redistributable Corpus Of 3rd-Party Simulink Models, Sohil Lal Shrestha, Shafiul Azam Chowdhury, Christoph Csallner
Association of Computing Machinery Open Access Agreement Publications
MATLAB/Simulink is widely used for model-based design. Engineers create Simulink models and compile them to embedded code, often to control safety-critical cyber-physical systems in automotive, aerospace, and healthcare applications. Despite Simulink's importance, there are few large-scale empirical Simulink studies, perhaps because there is no large readily available corpus of third-party open-source Simulink models. To enable empirical Simulink studies, this paper introduces SLNET, the largest corpus of freely available third-party Simulink models. SLNET has several advantages over earlier collections. Specifically, SLNET is 8 times larger than the largest previous corpus of Simulink models, includes finegrained metadata, is constructed automatically, is self-contained, …
Psdoodle: Searching For App Screens Via Interactive Sketching, Soumik Mohian, Christoph Csallner
Psdoodle: Searching For App Screens Via Interactive Sketching, Soumik Mohian, Christoph Csallner
Association of Computing Machinery Open Access Agreement Publications
Keyword-based mobile screen search does not account for screen content and fails to operate as a universal tool for all levels of users. Visual searching (e.g., image, sketch) is structured and easy to adopt. Current visual search approaches count on a complete screen and are therefore slow and tedious. PSDoodle employs a deep neural network to recognize partial screen element drawings instantly on a digital drawing interface and shows results in real-time. PSDoodle is the first tool that utilizes partial sketches and searches for screens in an interactive iterative way. PSDoodle supports different drawing styles and retrieves search results that …
Iotree: A Battery-Free Wearable System With Biocompatible Sensors For Continuous Tree Health Monitoring, Tuan Dang, Trung Tran, Khang Nguyen, Tien Pham, Nhat Pham, Tam Vu, Phuc Nguyen
Iotree: A Battery-Free Wearable System With Biocompatible Sensors For Continuous Tree Health Monitoring, Tuan Dang, Trung Tran, Khang Nguyen, Tien Pham, Nhat Pham, Tam Vu, Phuc Nguyen
Association of Computing Machinery Open Access Agreement Publications
In this paper, we present a low-maintenance, wind-powered, battery-free, biocompatible, tree wearable, and intelligent sensing system, namely IoTree, to monitor water and nutrient levels inside a living tree. IoTree system includes tiny-size, biocompatible, and implantable sensors that continuously measure the impedance variations inside the living tree's xylem, where water and nutrients are transported from the root to the upper parts. The collected data are then compressed and transmitted to a base station located at up to 1.8 kilometers (approximately 1.1 miles) away. The entire IoTree system is powered by wind energy and controlled by an adaptive computing technique called block-based …
Robust Self-Training Strategy For Various Molecular Biology Prediction Tasks∗, Hehuan Ma, Feng Jiang, Yu Rong, Yuzhi Guo, Junzhou Huang
Robust Self-Training Strategy For Various Molecular Biology Prediction Tasks∗, Hehuan Ma, Feng Jiang, Yu Rong, Yuzhi Guo, Junzhou Huang
Association of Computing Machinery Open Access Agreement Publications
Molecular biology prediction tasks suffer the limited labeled data problem since it normally demands a series of professional experiments to label the target molecule. Self-training is one of the semi-supervised learning paradigms that utilizes both labeled and unlabeled data. It trains a teacher model on labeled data, and uses it to generate pseudo labels for unlabeled data. The labeled and pseudo-labeled data are then combined to train a student model. However, the pseudo labels generated from the teacher model are not sufficiently accurate. Thus, we propose a robust self-training strategy by exploring robust loss function to handle such noisy labels, …
Modna: Motif-Oriented Pre-Training For Dna Language Model, Weizhi An, Yuzhi Guo, Yatao Bian, Hehuan Ma, Jinyu Yang, Chunyuan Li, Junzhou Huang
Modna: Motif-Oriented Pre-Training For Dna Language Model, Weizhi An, Yuzhi Guo, Yatao Bian, Hehuan Ma, Jinyu Yang, Chunyuan Li, Junzhou Huang
Association of Computing Machinery Open Access Agreement Publications
Obtaining informative representations of gene expression is crucial in predicting various downstream regulatory-related tasks such as promoter prediction and transcription factor binding sites prediction. Nevertheless, current supervised learning with insufficient labeled genomes limits the generalization capability of training a robust predictive model. Recently researchers model DNA sequences by self-supervised training and transfer the pre-trained genome representations to various downstream tasks. Instead of directly shifting the mask language learning to DNA sequence learning, we incorporate prior knowledge into genome language modeling representations. We propose a novel Motif-oriented DNA (MoDNA) pre-training framework, which is designed self-supervised and can be fine-tuned for different …
Towards Automated Input Generation For Sketching Alloy Models, Ana Jovanovic, Allison Sullivan
Towards Automated Input Generation For Sketching Alloy Models, Ana Jovanovic, Allison Sullivan
Association of Computing Machinery Open Access Agreement Publications
Writing declarative models has numerous benefits, ranging from automated reasoning and correction of design-level properties before systems are built, to automated testing and debugging of their implementations after they are built. Alloy is a declarative modeling language that is well suited for verifying system designs. While Alloy comes deployed in the Analyzer, an automated scenario-finding tool set, writing correct models remains a difficult and error-prone task. ASketch is a synthesis framework that helps users build their Alloy models. ASketch takes as an input a partial Alloy models with holes and an AUnit test suite. As output, ASketch returns a completed …
An Investigation Of Quantitative Measures Of Sleep-Apnea-Induced Nocturnal Cardiac Stress, Pegah Askari, Mahrshi B. Jani, Donald E. Watenpaugh, Khosrow Behbehani
An Investigation Of Quantitative Measures Of Sleep-Apnea-Induced Nocturnal Cardiac Stress, Pegah Askari, Mahrshi B. Jani, Donald E. Watenpaugh, Khosrow Behbehani
Association of Computing Machinery Open Access Agreement Publications
Obstructive Sleep Apnea (OSA) affects an estimated 18 million individuals in the U.S. adult population. Numerous research findings indicate that OSA has significant adverse effects on the cardiac health. Current method of assessing the severity of OSA using apnea hypopnea index (AHI) which is the average count of apneic events per hour of sleep does not reflect how OSA affects the cardiovascular system health. In this study, we investigate the possibility of analyzing the nocturnal Electrocardiography (ECG) signal to assess the adverse impact of sleep apnea events on the heart. Our approach focuses on determining whether nocturnal cardiac arrhythmia is …
Automated System To Measure Static Balancing In Children To Assess Executive Function, Hamza Reza Pavel, Enamul Karim, Mohammad Zaki Zadeh, Ashish Jaiswal, Rithik Kapoor, Fillia Makedon
Automated System To Measure Static Balancing In Children To Assess Executive Function, Hamza Reza Pavel, Enamul Karim, Mohammad Zaki Zadeh, Ashish Jaiswal, Rithik Kapoor, Fillia Makedon
Association of Computing Machinery Open Access Agreement Publications
We present multiple methods based on computer vision and deep learning to automate the task of ”Balancing on one foot”. This is one of the Activate Test of Embodied Cognition (ATEC) tasks used to measure cognitive skills in children through physical activity. A dataset of 27 children performing the ATEC task is used to train and validate the deep learning models used to automate the task. As opposed to most balance identification systems that use sensors, our proposed approach relies only on computer vision which can be easily deployed at home or classroom environment, is portable, and cheap. Our proposed …
Smartphone Based Iot-Controller Framework For Assisting The Blind In Human Robot Interaction, Harish Ram Nambiappan, Enamul Karim, Md Jillur Rahman Saurav, Anushka Srivastav, Nicholas Gans, Fillia Makedon
Smartphone Based Iot-Controller Framework For Assisting The Blind In Human Robot Interaction, Harish Ram Nambiappan, Enamul Karim, Md Jillur Rahman Saurav, Anushka Srivastav, Nicholas Gans, Fillia Makedon
Association of Computing Machinery Open Access Agreement Publications
In this paper, a novel smartphone-based IoT-Controller Framework is proposed for effective interaction between robots and people who are blind. This framework focuses on assisting visually impaired users in a pick and place task scenario in contrast to previous works, which primarily focus on navigation and localization. The user can give speech commands to the robot using a smartphone application, which is sent to a server for recognition and retrieval of information such as positions and type of object to be grasped. The details are sent to the robot, which performs the commanded task. Preliminary tests with five participants over …
Light-Weight Seated Posture Guidance System With Machine Learning And Computer Vision, Rithik Kapoor, Ashish Jaiswal, Fillia Makedon
Light-Weight Seated Posture Guidance System With Machine Learning And Computer Vision, Rithik Kapoor, Ashish Jaiswal, Fillia Makedon
Association of Computing Machinery Open Access Agreement Publications
In today’s world, the increased time people spend in front of their computers has been one of the main causes for neck and back pains. Especially, since the pandemic, it has been quite evident that slouching at home for long hours on hand-held devices and computers has led many people towards spinal pains and injuries. Backed with scientific research, it has been proven that these pains can be prevented with proper monitoring of the seated posture and taking breaks in between. This paper focuses on building a light-weight end-to-end system that monitors the user’s posture and provides feedback whenever it …
Large-Scale Self-Supervised Human Activity Recognition, Mohammad Zaki Zadeh, Ashish Jaiswal, Hamza Reza Pavel, Aref Hebri, Rithik Kapoor, Fillia Makedon
Large-Scale Self-Supervised Human Activity Recognition, Mohammad Zaki Zadeh, Ashish Jaiswal, Hamza Reza Pavel, Aref Hebri, Rithik Kapoor, Fillia Makedon
Association of Computing Machinery Open Access Agreement Publications
In this paper, a self-supervised approach is used to obtain an effective human activity representation using a limited set of annotated data. This research is aimed on acquiring human activity representation in order to improve the accuracy of classifying videos of human activities in the NTU RGB+D 120 dataset. The effectiveness of various self-supervised approaches, as well as a supervised method, is studied. The results reveal that when the training set gets smaller, the performance of supervised learning approaches diminishes, whereas self-supervised methods maintain their performance by utilizing unlabeled data.
Person Identification And Tinetti Score Prediction Using Balance Parameters : A Machine Learning Approach To Determine Fall Risk, Varsha Rani Chawan, Manfred Huber, Nicholas Burns, Kathryn Daniel
Person Identification And Tinetti Score Prediction Using Balance Parameters : A Machine Learning Approach To Determine Fall Risk, Varsha Rani Chawan, Manfred Huber, Nicholas Burns, Kathryn Daniel
Association of Computing Machinery Open Access Agreement Publications
This paper presents a Machine Learning approach using sensor data from a Smart Floor aimed at addressing a substantial health problem among the elderly population, namely falls. Studies show that one-third of community-dwelling people over age 65 will experience one or more falls each year. Balance and walking patterns are useful indicators to determine the fall risk and are influenced by several parameters and conditions. The Tinetti test is widely used to assess the gait and balance in elder adults to determine the perception of balance and stability during daily activities and fear of falling. It is considered a good …
Classification Of Alzheimer's Disease Via Vision Transformer: Classification Of Alzheimer's Disease Via Vision Transformer, Yanjun Lyu, Xiaowei Yu, Dajiang Zhu, Lu Zhang
Classification Of Alzheimer's Disease Via Vision Transformer: Classification Of Alzheimer's Disease Via Vision Transformer, Yanjun Lyu, Xiaowei Yu, Dajiang Zhu, Lu Zhang
Association of Computing Machinery Open Access Agreement Publications
Deep models are powerful in capturing the complex and non-linear relationship buried in brain imaging data. However, the huge number of parameters in deep models can easily overfit given limited imaging data samples. In this work, we proposed a cross-domain transfer learning method to solve the insufficient data problem in brain imaging domain by leveraging the knowledge learned in natural image domain. Specifically, we employed ViT as the backbone and firstly pretrained it using ImageNet-21K dataset and then transferred to the brain imaging dataset. A slice-wise convolution embedding method was developed to improve the standard patch operation in vanilla ViT. …
Gan-Based Face Reconstruction For Masked-Face, Farnaz Farahanipad, Mohammad Rezaei, Mohammadsadegh Nasr, Farhad Kamangar, Vassilis Athitsos
Gan-Based Face Reconstruction For Masked-Face, Farnaz Farahanipad, Mohammad Rezaei, Mohammadsadegh Nasr, Farhad Kamangar, Vassilis Athitsos
Association of Computing Machinery Open Access Agreement Publications
Facial recognition and identification which play an important role in human-computer interaction, secure authentication and criminal face recognition, are impeded by the advent of face masks due to COVID-19 pandemic. This is a challenging problem due to the following reasons: (i) masks cover quite a large part of the face even below the chin, (ii) it is not possible to collect and prepare a real paired-face images with and without mask object, (iii) face alterations and the presence of different masks is even more challenging. In this work, we propose a general framework that can be used to reconstruct the …
Practical Efficient Microservice Autoscaling With Qos Assurance, Md Rajib Hossen, Mohammad A. Islam, Kishwar Ahmed
Practical Efficient Microservice Autoscaling With Qos Assurance, Md Rajib Hossen, Mohammad A. Islam, Kishwar Ahmed
Association of Computing Machinery Open Access Agreement Publications
Cloud applications are increasingly moving away from monolithic services to agile microservices-based deployments. However, efficient resource management for microservices poses a significant hurdle due to the sheer number of loosely coupled and interacting components. The interdependencies between various microservices make existing cloud resource autoscaling techniques ineffective. Meanwhile, machine learning (ML) based approaches that try to capture the complex relationships in microservices require extensive training data and cause intentional SLO violations. Moreover, these ML-heavy approaches are slow in adapting to dynamically changing microservice operating environments. In this paper, we propose PEMA (Practical Efficient Microservice Autoscaling), a lightweight microservice resource manager that …
Embr: A Creative Framework For Hand Embroidered Liquid Crystal Textile Displays, Shreyosi Endow, Mohammad Abu Nasir Rakib, Anvay Srivastava, Sara Rastegarpouyani, Cesar Torres
Embr: A Creative Framework For Hand Embroidered Liquid Crystal Textile Displays, Shreyosi Endow, Mohammad Abu Nasir Rakib, Anvay Srivastava, Sara Rastegarpouyani, Cesar Torres
Association of Computing Machinery Open Access Agreement Publications
Conductive thread is a common material in e-textile toolkits that allows practitioners to create connections between electronic components sewn on fabric. When powered, conductive threads are used as resistive heaters to activate thermochromic dyes or pigments on textiles to create interactive, aesthetic, and ambient textile displays. In this work, we introduce Embr, a creative framework for supporting hand-embroidered liquid crystal textile displays (LCTDs). This framework includes a characterization of conductive embroidery stitches, an expanded repertoire of thermal formgiving techniques, and a thread modeling tool used to simulate mechanical, thermal, and electrical behaviors of LCTDs. Through exemplar artifacts, we annotate a …
Improving Scalability Of Database Systems By Reshaping User Parallel I/O, Ning Li, Hong Jiang, Hao Che, Zhijun Wang, Minh Q. Nguyen
Improving Scalability Of Database Systems By Reshaping User Parallel I/O, Ning Li, Hong Jiang, Hao Che, Zhijun Wang, Minh Q. Nguyen
Association of Computing Machinery Open Access Agreement Publications
Modern database systems suffer from compromised throughput, persistent unfair I/O processing and unpredictable, high latency variability of user requests as a result of mismatches between highly scaled user parallel I/O and the I/O capacity afforded by the database and its underlying storage I/O stack. To address this problem, we introduce an efficient user-centric QoS-aware scheduling shim, called AppleS, for user-level fine-grained I/O regulation that delivers the right amount and pattern of user parallel I/O requests to the database system and supports user SLOs with high-level performance isolation and reduced I/O resource contention. It is designed to enable database systems to …
Characterizing The Performance Of Intel Optane Persistent Memory, Xiang Lingfeng, Xingsheng Zhao, Jia Rao, Song Jiang, Hong Jiang
Characterizing The Performance Of Intel Optane Persistent Memory, Xiang Lingfeng, Xingsheng Zhao, Jia Rao, Song Jiang, Hong Jiang
Association of Computing Machinery Open Access Agreement Publications
We present a comprehensive and in-depth study of Intel Optane DC persistent memory (DCPMM). Our focus is on exploring the internal design of Optane’s on-DIMM readwrite buffering and its impacts on application-perceived performance, read and write amplifications, the overhead of different types of persists, and the tradeoffs between persistency models. While our measurements confirm the results of the existing profiling studies, we have new discoveries and offer new insights. Notably, we find that read and write are managed differently in separate on-DIMM read and write buffers. Comparable in size, the two buffers serve distinct purposes. The read buffer offers higher …
Eyeqoe: A Novel Qoe Assessment Model For 360-Degree Videos Using Ocular Behaviors, Huadi Zhu, Tianhao Li, Chaowei Wang, Wenqiang Jin, Srinivasan Murali, Mingyan Xiao, Dongqing Ye, Ming Li
Eyeqoe: A Novel Qoe Assessment Model For 360-Degree Videos Using Ocular Behaviors, Huadi Zhu, Tianhao Li, Chaowei Wang, Wenqiang Jin, Srinivasan Murali, Mingyan Xiao, Dongqing Ye, Ming Li
Association of Computing Machinery Open Access Agreement Publications
As virtual reality (VR) offers an unprecedented experience than any existing multimedia technologies, VR videos, or called 360-degree videos, have attracted considerable attention from academia and industry. How to quantify and model end users' perceived quality in watching 360-degree videos, or called QoE, resides the center for high-quality provisioning of these multimedia services. In this work, we present EyeQoE, a novel QoE assessment model for 360-degree videos using ocular behaviors. Unlike prior approaches, which mostly rely on objective factors, EyeQoE leverages the new ocular sensing modality to comprehensively capture both subjective and objective impact factors for QoE modeling. We propose …
One Size Does Not Fit All: Security Hardening Of Mips Embedded Systems Via Static Binary Debloating For Shared Libraries, Haotian Zhang, Mengfei Ren, Yu Lei, Jiang Ming
One Size Does Not Fit All: Security Hardening Of Mips Embedded Systems Via Static Binary Debloating For Shared Libraries, Haotian Zhang, Mengfei Ren, Yu Lei, Jiang Ming
Association of Computing Machinery Open Access Agreement Publications
Embedded systems have become prominent targets for cyberattacks. To exploit firmware’s memory corruption vulnerabilities, cybercriminals harvest reusable code gadgets from the large shared library codebase (e.g., uClibc). Unfortunately, unlike their desktop counterparts, embedded systems lack essential computing resources to enforce security hardening techniques. Recently, we have witnessed a surge of software debloating as a new defense mechanism against code-reuse attacks; it erases unused code to significantly diminish the possibilities of constructing reusable gadgets. Because of the single firmware image update style, static library debloating shows promise to fortify embedded systems without compromising performance and forward compatibility. However, static library debloating …
Glaze Epochs: Understanding Lifelong Material Relationships Within Ceramics Studios, Hedieh Moradi, Long N. Nguyen, Quyen Anh Valentina Nguyen, Cesar Torres
Glaze Epochs: Understanding Lifelong Material Relationships Within Ceramics Studios, Hedieh Moradi, Long N. Nguyen, Quyen Anh Valentina Nguyen, Cesar Torres
Association of Computing Machinery Open Access Agreement Publications
The “material turn” in HCI has placed a renewed focus on informing design from the relationships found in material-based interactions. While several ethnographic works provide insight into how practitioners converse with materials, it is less understood how these conversations transform into a skilled practitioner’s relationship with a material. We examine the material practice of glazing that gives ceramics its decorative and functional characteristics and involves fusing mixtures of silica, alumina, and flux onto a clay body through kiln firing. This practice evolves over decades developing from multiple trajectories including theoretical foundations, systematic experimentation, and happy accidents. This work describes virtual …