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- 1.2 COMPUTER AND INFORMATION SCIENCE (3)
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Articles 1 - 24 of 24
Full-Text Articles in Engineering
Identifying Depressive Symptoms From Tweets: Figurative Language Enabled Multitask Learning Framework, Shweta Yadav, Jainish Chauhan, Joy Prakash Sain, Krishnaprasad Thirunarayan, Amit P. Sheth, Jeremiah Schumm
Identifying Depressive Symptoms From Tweets: Figurative Language Enabled Multitask Learning Framework, Shweta Yadav, Jainish Chauhan, Joy Prakash Sain, Krishnaprasad Thirunarayan, Amit P. Sheth, Jeremiah Schumm
Publications
Existing studies on using social media for deriving mental health status of users focus on the depression detection task. However, for case management and referral to psychiatrists, healthcare workers require practical and scalable depressive disorder screening and triage system. This study aims to design and evaluate a decision support system (DSS) to reliably determine the depressive triage level by capturing fine-grained depressive symptoms expressed in user tweets through the emulation of Patient Health Questionnaire-9 (PHQ-9) that is routinely used in clinical practice. The reliable detection of depressive symptoms from tweets is challenging because the 280-character limit on tweets incentivizes the …
Medical Knowledge-Enriched Textual Entailment Framework, Shweta Yadav, Vishal Pallagani, Amit P. Sheth
Medical Knowledge-Enriched Textual Entailment Framework, Shweta Yadav, Vishal Pallagani, Amit P. Sheth
Publications
One of the cardinal tasks in achieving robust medical question answering systems is textual entailment. The existing approaches make use of an ensemble of pre-trained language models or data augmentation, often to clock higher numbers on the validation metrics. However, two major shortcomings impede higher success in identifying entailment: (1) understanding the focus/intent of the question and (2) ability to utilize the real-world background knowledge to capture the context beyond the sentence. In this paper, we present a novel Medical Knowledge-Enriched Textual Entailment framework that allows the model to acquire a semantic and global representation of the input medical text …
Covid-19 In Spain And India: Comparing Policy Implications By Analyzing Epidemiological And Social Media Data, Parth Asawa, Manas Gaur, Kaushik Roy, Amit P. Sheth
Covid-19 In Spain And India: Comparing Policy Implications By Analyzing Epidemiological And Social Media Data, Parth Asawa, Manas Gaur, Kaushik Roy, Amit P. Sheth
Publications
The COVID-19 pandemic has forced public health experts to develop contingent policies to stem the spread of infection, including measures such as partial/complete lockdowns. The effectiveness of these policies has varied with geography, population distribution, and effectiveness in implementation. Consequently, some nations (e.g., Taiwan, Haiti) have been more successful than others (e.g., United States) in curbing the outbreak. A data-driven investigation into effective public health policies of a country would allow public health experts in other nations to decide future courses of action to control the outbreaks of disease and epidemics. We chose Spain and India to present our analysis …
Enterprise Architecture Transformation Process From A Federal Government Perspective, Tonia Canada, Leila Halawi
Enterprise Architecture Transformation Process From A Federal Government Perspective, Tonia Canada, Leila Halawi
Publications
The need for information technology organizations to transform enterprise architecture is driven by federal government mandates and information technology budget constraints. This qualitative case study aimed to identify factors that hinder federal government agencies from driving enterprise architecture transformation processes from a compliancy to a flexible process. Common themes in interviewee responses were identified, coded, and summarized. Critical recommendations for future best practices, including further research, were also presented.
Finite-Time State Estimation For An Inverted Pendulum Under Input-Multiplicative Uncertainty, Sergey V. Drakunov, William Mackunis, Anu Kossery Jayaprakash, Krishna Bhavithavya Kidambi, Mahmut Reyhanoglu
Finite-Time State Estimation For An Inverted Pendulum Under Input-Multiplicative Uncertainty, Sergey V. Drakunov, William Mackunis, Anu Kossery Jayaprakash, Krishna Bhavithavya Kidambi, Mahmut Reyhanoglu
Publications
A sliding mode observer is presented, which is rigorously proven to achieve finite-time state estimation of a dual-parallel underactuated (i.e., single-input multi-output) cart inverted pendulum system in the presence of parametric uncertainty. A salient feature of the proposed sliding mode observer design is that a rigorous analysis is provided, which proves finite-time estimation of the complete system state in the presence of input-multiplicative parametric uncertainty. The performance of the proposed observer design is demonstrated through numerical case studies using both sliding mode control (SMC)- and linear quadratic regulator (LQR)-based closed-loop control systems. The main contribution presented here is the rigorous …
Cyber Social Threats 2020 Workshop Meta-Report: Covid-19, Challenges, Methodological And Ethical Considerations, Ugur Kursuncu, Yelena Mejova, Jeremy Blackburn, Amit Sheth
Cyber Social Threats 2020 Workshop Meta-Report: Covid-19, Challenges, Methodological And Ethical Considerations, Ugur Kursuncu, Yelena Mejova, Jeremy Blackburn, Amit Sheth
Publications
Online platforms have been increasingly misused by ill-intentioned actors, affecting our society, often leading to real-world events of social significance. On the other hand, recog-nizing the narratives related to harmful behaviors is challeng-ing due to its complex and sensitive nature. The Cyber SocialThreats Workshop 2020 aimed to stimulate research for thechallenges on methodological and ethical considerations indeveloping novel approaches to analyze online harmful con-versations, concerning social, cultural, emotional, commu-nicative, and linguistic aspects. It provided a forum to bringtogether researchers and practitioners from both academiaand industry in the areas of computational social sciences, so-cial network analysis and mining, natural language process-ing, …
Zero-Bias Deep Learning For Accurate Identification Of Internet Of Things (Iot) Devices, Yongxin Liu, Houbing Song, Thomas Yang, Jian Wang, Jianqiang Li, Shuteng Niu, Zhong Ming
Zero-Bias Deep Learning For Accurate Identification Of Internet Of Things (Iot) Devices, Yongxin Liu, Houbing Song, Thomas Yang, Jian Wang, Jianqiang Li, Shuteng Niu, Zhong Ming
Publications
The Internet of Things (IoT) provides applications and services that would otherwise not be possible. However, the open nature of IoT makes it vulnerable to cybersecurity threats. Especially, identity spoofing attacks, where an adversary passively listens to the existing radio communications and then mimic the identity of legitimate devices to conduct malicious activities. Existing solutions employ cryptographic signatures to verify the trustworthiness of received information. In prevalent IoT, secret keys for cryptography can potentially be disclosed and disable the verification mechanism. Noncryptographic device verification is needed to ensure trustworthy IoT. In this article, we propose an enhanced deep learning framework …
Is It Safe For My Child’S Asthma?, Utkarshani Jaimini, Amit Sheth, Krishnaprasad Thirunarayan, Maninder Kalra, Marco Valtorta
Is It Safe For My Child’S Asthma?, Utkarshani Jaimini, Amit Sheth, Krishnaprasad Thirunarayan, Maninder Kalra, Marco Valtorta
Publications
kHealth-Asthma, a personalised digital healthcare framework is developed to address the above shortcomings by continuous monitoring of the child’s digital phenotype, indoor, and outdoor environmental data. The kHealth-Asthma study has recruited 140 children (ongoing) with an aim to complete recruitment of 150 children. The study period is either 1 month or 3 month depending on the choice of the study participant. kHealth-Asthma collects 29 multi-modal parameters leading to 1852 data points per patient per day (i.e. deployment: 1 month:1852*30=55,560 data points per patient and 3 month:1852*90=166,680 data points per patient). The digital phenotype collected using the kHealth-Asthma generates a Digital …
Multimodal Mental Health Analysis In Social Media, Amir Hossein Yazdavar, Mohammad Saeid Mahdavinejad, Goonmeet Bajaj, William Romine, Amit P. Sheth, Amir Hassan Monadjemi, Krishnaprasad Thirunarayan, John M. Meddar, Annie Myers, Jyotishman Pathak, Pascal Hitzler
Multimodal Mental Health Analysis In Social Media, Amir Hossein Yazdavar, Mohammad Saeid Mahdavinejad, Goonmeet Bajaj, William Romine, Amit P. Sheth, Amir Hassan Monadjemi, Krishnaprasad Thirunarayan, John M. Meddar, Annie Myers, Jyotishman Pathak, Pascal Hitzler
Publications
Depression is a major public health concern in the U.S. and globally. While successful early identification and treatment can lead to many positive health and behavioral outcomes, depression, remains undiagnosed, untreated or undertreated due to several reasons, including denial of the illness as well as cultural and social stigma. With the ubiquity of social media platforms, millions of people are now sharing their online persona by expressing their thoughts, moods, emotions, and even their daily struggles with mental health on social media. Unlike traditional observational cohort studies conducted through questionnaires and self-reported surveys, we explore the reliable detection of depressive …
Analyzing And Learning The Language For Different Types Of Harassment, Mohammadreza Rezvan, Saeedeh Shekarpour, Faisal Alshargi, Krishnaprasad Thirunarayan, Valerie L. Shalin, Amit P. Sheth
Analyzing And Learning The Language For Different Types Of Harassment, Mohammadreza Rezvan, Saeedeh Shekarpour, Faisal Alshargi, Krishnaprasad Thirunarayan, Valerie L. Shalin, Amit P. Sheth
Publications
THIS ARTICLE USES WORDS OR LANGUAGE THAT IS CONSIDERED PROFANE, VULGAR, OR OFFENSIVE BY SOME READERS. The presence of a significant amount of harassment in user-generated content and its negative impact calls for robust automatic detection approaches. This requires the identification of different types of harassment. Earlier work has classified harassing language in terms of hurtfulness, abusiveness, sentiment, and profanity. However, to identify and understand harassment more accurately, it is essential to determine the contextual type that captures the interrelated conditions in which harassing language occurs. In this paper we introduce the notion of contextual type in harassment by distinguishing …
Knowledge Infused Learning (K-Il): Towards Deep Incorporation Of Knowledge In Deep Learning, Ugur Kursuncu, Manas Gaur, Amit Sheth
Knowledge Infused Learning (K-Il): Towards Deep Incorporation Of Knowledge In Deep Learning, Ugur Kursuncu, Manas Gaur, Amit Sheth
Publications
Learning the underlying patterns in data goes beyondinstance-based generalization to external knowledge repre-sented in structured graphs or networks. Deep learning thatprimarily constitutes neural computing stream in AI hasshown significant advances in probabilistically learning la-tent patterns using a multi-layered network of computationalnodes (i.e., neurons/hidden units). Structured knowledge thatunderlies symbolic computing approaches and often supportsreasoning, has also seen significant growth in recent years,in the form of broad-based (e.g., DBPedia, Yago) and do-main, industry or application specific knowledge graphs. Acommon substrate with careful integration of the two willraise opportunities to develop neuro-symbolic learning ap-proaches for AI, where conceptual and probabilistic repre-sentations are combined. …
System Level Model For Pumped Two-Phase Cooling Systems, Leitao Chen, Timothy Joseph Chainer, Pritish Ranjan Parida, Mark Delorman Schultz, Fanghao Yang
System Level Model For Pumped Two-Phase Cooling Systems, Leitao Chen, Timothy Joseph Chainer, Pritish Ranjan Parida, Mark Delorman Schultz, Fanghao Yang
Publications
Techniques are provided for system level modeling of two-phase cooling systems. In one example, a computer implemented method comprises determining, by a system operatively coupled to a processor, respective sets of steady state values for parameters at inlet-outlet junctions using a system model, wherein the determining is based on first user input specifying a cooling system design comprising a plurality of part objects, wherein adjacent part objects in a flow direction are connected at the inlet-outlet junctions. The computer-implemented method can also comprise generating, by the system, a graphical display that depicts the respective sets of parameter values at the …
W-Gun: Whale Optimization For Energy And Delay-Centric Green Underwater Networks, Rajkumar Singh Rathore, Houbing Song, Suman Sangwan, Sukriti Mazumdar, Omprakash Kaiwartya, Kabita Adhikari, Rupak Kharel
W-Gun: Whale Optimization For Energy And Delay-Centric Green Underwater Networks, Rajkumar Singh Rathore, Houbing Song, Suman Sangwan, Sukriti Mazumdar, Omprakash Kaiwartya, Kabita Adhikari, Rupak Kharel
Publications
Underwater sensor networks (UWSNs) have witnessed significant R&D attention in both academia and industry due to their growing application domains, such as border security, freight via sea or river, natural petroleum production and the fishing industry. Considering the deep underwater-oriented access constraints, energy-centric communication for the lifetime maximization of tiny sensor nodes in UWSNs is one of the key research themes in this domain. Existing literature on green UWSNs are majorly adapted from the existing techniques in traditional wireless sensor network relying on geolocation and the quality of service-centric underwater relay node selection, without paying much attention to the dynamic …
Deal: Differentially Private Auction For Blockchain Based Microgrids Energy Trading, Muneeb Ul Hassan, Mubashir Husain Rehmani, Jinjun Chen
Deal: Differentially Private Auction For Blockchain Based Microgrids Energy Trading, Muneeb Ul Hassan, Mubashir Husain Rehmani, Jinjun Chen
Publications
Modern smart homes are being equipped with certain renewable energy resources that can produce their own electric energy. From time to time, these smart homes or microgrids are also capable of supplying energy to other houses, buildings, or energy grid in the time of available self-produced renewable energy. Therefore, researches have been carried out to develop optimal trading strategies, and many recent technologies are also being used in combination with microgrids. One such technology is blockchain, which works over decentralized distributed ledger. In this paper, we develop a blockchain based approach for microgrid energy auction. To make this auction more …
Differential Privacy Techniques For Cyber Physical Systems: A Survey, Muneeb Ul Hassan, Mubashir Husain Rehmani, Jinjun Chen
Differential Privacy Techniques For Cyber Physical Systems: A Survey, Muneeb Ul Hassan, Mubashir Husain Rehmani, Jinjun Chen
Publications
Modern cyber physical systems (CPSs) has widely being used in our daily lives because of development of information and communication technologies (ICT).With the provision of CPSs, the security and privacy threats associated to these systems are also increasing. Passive attacks are being used by intruders to get access to private information of CPSs. In order to make CPSs data more secure, certain privacy preservation strategies such as encryption, and k-anonymity have been presented in the past. However, with the advances in CPSs architecture, these techniques also need certain modifications. Meanwhile, differential privacy emerged as an efficient technique to protect CPSs …
Piecing Together Summon Over Alma Documentation, James M. Day
Piecing Together Summon Over Alma Documentation, James M. Day
Publications
Ex Libris provides some useful documentation for “Alma-Summon Integration” but it is not complete. Most Alma documentation and online help pages assume you are using Primo. Sometimes the Alma configurations for Primo apply to Summon, but mostly they do not. The ELUNA Summon Product Working Group members using Summon over Alma started a project to identify existing documentation, consolidate it, and create supplemental documentation where necessary. We hope this will help Ex Libris provide better support for Summon over Alma.
Cache-Enabled In Cooperative Cognitive Radio Networks For Transmission Performance, Jiachen Yang, Houbing Song, Chaofan Ma, Jiabao Man, Huifang Xu, Gan Zheng
Cache-Enabled In Cooperative Cognitive Radio Networks For Transmission Performance, Jiachen Yang, Houbing Song, Chaofan Ma, Jiabao Man, Huifang Xu, Gan Zheng
Publications
The proliferation of mobile devices that support the acceleration of data services (especially smartphones) has resulted in a dramatic increase in mobile traffic. Mobile data also increased exponentially, already exceeding the throughput of the backhaul. To improve spectrum utilization and increase mobile network traffic, in combination with content caching, we study the cooperation between primary and secondary networks via content caching. We consider that the secondary base station assists the primary user by pre-caching some popular primary contents. Thus, the secondary base station can obtain more licensed bandwidth to serve its own user. We mainly focus on the time delay …
Coverage Guided Differential Adversarial Testing Of Deep Learning Systems, Jianmin Guo, Houbing Song, Yue Zhao, Yu Jiang
Coverage Guided Differential Adversarial Testing Of Deep Learning Systems, Jianmin Guo, Houbing Song, Yue Zhao, Yu Jiang
Publications
Deep learning is increasingly applied to safety-critical application domains such as autonomous cars and medical devices. It is of significant importance to ensure their reliability and robustness. In this paper, we propose DLFuzz, the coverage guided differential adversarial testing framework to guide deep learing systems exposing incorrect behaviors. DLFuzz keeps minutely mutating the input to maximize the neuron coverage and the prediction difference between the original input and the mutated input, without manual labeling effort or cross-referencing oracles from other systems with the same functionality. We also design multiple novel strategies for neuron selection to improve the neuron coverage. The …
Alone: A Dataset For Toxic Behavior Among Adolescents On Twitter, Thilini Wijesiriwardene, Hale Inan, Ugur Kursuncu, Manas Gaur, Valerie L. Shalin, Krishnaprasad Thirunarayan, Amit P. Sheth, I. Budak Arpinar
Alone: A Dataset For Toxic Behavior Among Adolescents On Twitter, Thilini Wijesiriwardene, Hale Inan, Ugur Kursuncu, Manas Gaur, Valerie L. Shalin, Krishnaprasad Thirunarayan, Amit P. Sheth, I. Budak Arpinar
Publications
The convenience of social media has also enabled its misuse, potentially resulting in toxic behavior. Nearly 66% of internet users have observed online harassment, and 41% claim personal experience, with 18% facing severe forms of online harassment. This toxic communication has a significant impact on the well-being of young individuals, affecting mental health and, in some cases, resulting in suicide. These communications exhibit complex linguistic and contextual characteristics, making recognition of such narratives challenging. In this paper, we provide a multimodal dataset of toxic social media interactions between confirmed high school students, called ALONE (AdoLescents ON twittEr), along with descriptive …
Explainable Ai Using Knowledge Graphs, Manas Gaur, Ankit Desai, Keyur Faldu, Amit Sheth
Explainable Ai Using Knowledge Graphs, Manas Gaur, Ankit Desai, Keyur Faldu, Amit Sheth
Publications
During the last decade, traditional data-driven deep learning (DL) has shown remarkable success in essential natural language processing tasks, such as relation extraction. Yet, challenges remain in developing artificial intelligence (AI) methods in real-world cases that require explainability through human interpretable and traceable outcomes. The scarcity of labeled data for downstream supervised tasks and entangled embeddings produced as an outcome of self-supervised pre-training objectives also hinders interpretability and explainability. Additionally, data labeling in multiple unstructured domains, particularly healthcare and education, is computationally expensive as it requires a pool of human expertise. Consider Education Technology, where AI systems fall along a …
Relational Sequential Decision Making, Kaushik Roy
Relational Sequential Decision Making, Kaushik Roy
Publications
Markov Decision Processes(MDPs) are the standard for sequential decision making. Comprehensive theory and methods have been developed to deal with solving MDPs in the propositional setting. Real world domains however are naturally represented using objects and relationships. To this effect, relational adaptations of algorithms to solve MDPs have been proposed in recent years. This paper presents a study of these techniques both in the model based and model free setting.
Mac Protocols For Terahertz Communication: A Comprehensive Survey, Saim Ghafoor, Noureddine Boujnah, Mubashir Husain Rehmani, Alan Davy
Mac Protocols For Terahertz Communication: A Comprehensive Survey, Saim Ghafoor, Noureddine Boujnah, Mubashir Husain Rehmani, Alan Davy
Publications
Terahertz communication is emerging as a future technology to support Terabits per second link with highlighting features as high throughput and negligible latency. However, the unique features of the Terahertz band such as high path loss, scattering, and reflection pose new challenges and results in short communication distance. The antenna directionality, in turn, is required to enhance the communication distance and to overcome the high path loss. However, these features in combine negate the use of traditional medium access protocols (MAC). Therefore, novel MAC protocol designs are required to fully exploit their potential benefits including efficient channel access, control message …
Assessing The Severity Of Health States Based On Social Media Posts, Shweta Yadav, Joy Prakash Sain, Amit P. Sheth, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya
Assessing The Severity Of Health States Based On Social Media Posts, Shweta Yadav, Joy Prakash Sain, Amit P. Sheth, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya
Publications
The unprecedented growth of Internet users has resulted in an abundance of unstructured information on social media including health forums, where patients request healthrelated information or opinions from other users. Previous studies have shown that online peer support has limited effectiveness without expert intervention. Therefore, a system capable of assessing the severity of health state from the patients’ social media posts can help health professionals (HP) in prioritizing the user’s post. In this study, we inspect the efficacy of different aspects of Natural Language Understanding (NLU) to identify the severity of the user’s health state in relation to two perspectives(tasks) …
Knowledge-Infused Statistical Learning For Social Good, Kaushik Roy, Manas Gaur
Knowledge-Infused Statistical Learning For Social Good, Kaushik Roy, Manas Gaur
Publications
Humans are able to provide symbolic knowledge in structured form for potential use by an AI system in learning human-desirable concepts. In clinical settings, for instance, prediction of patient outcomes by an AI can be guided by knowledge from patient history. This history contains concepts such as treatment information, observational and drug-related information, mental health conditions, and severity of disease/disorder. Additionally, there is also often a certain graphical structure to the knowledge among the concepts, for example, ”patient symptoms cause certain tests to be taken”, which in turn affects the prescription of medication. This type of structure between human interpretable …