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  • Beyond STEM, How Can Women Engage Big Data, Analytics, Robotics and Artificial Intelligence? An Exploratory Analysis of Confidence and Educational Factors in the Emerging Technology Waves Influencing the Role of, and Impact Upon, Women
    arXiv.cs.CY Pub Date : 2020-03-26
    Yana Samuel; Jean George; Jim Samuel

    In spite of the rapidly advancing global technological environment, the professional participation of women in technology, big data, analytics, artificial intelligence and information systems related domains remains proportionately low. Furthermore, it is of no less concern that the number of women in leadership in these domains are in even lower proportions. In spite of numerous initiatives to improve

    更新日期:2020-03-27
  • Falling into the Echo Chamber: the Italian Vaccination Debate on Twitter
    arXiv.cs.CY Pub Date : 2020-03-26
    Alessandro Cossard; Gianmarco De Francisci Morales; Kyriaki Kalimeri; Yelena Mejova; Daniela Paolotti; Michele Starnini

    The reappearance of measles in the US and Europe, a disease considered eliminated in early 2000s, has been accompanied by a growing debate on the merits of vaccination on social media. In this study we examine the extent to which the vaccination debate on Twitter is conductive to potential outreach to the vaccination hesitant. We focus on Italy, one of the countries most affected by the latest measles

    更新日期:2020-03-27
  • Development of a Real-time Indoor Location System using Bluetooth Low Energy Technology and Deep Learning to Facilitate Clinical Applications
    arXiv.cs.CY Pub Date : 2019-07-24
    Guanglin Tang; Yulong Yan; Chenyang Shen; Xun Jia; Meyer Zinn; Zipalkumar Trivedi; Alicia Yingling; Kenneth Westover; Steve Jiang

    An indoor, real-time location system (RTLS) can benefit both hospitals and patients by improving clinical efficiency through data-driven optimization of procedures. Bluetooth-based RTLS systems are cost-effective but lack accuracy and robustness because Bluetooth signal strength is subject to fluctuation. We developed a machine learning-based solution using a Long Short-Term Memory (LSTM) network followed

    更新日期:2020-03-27
  • Towards an Insightful Computer Security Seminar
    arXiv.cs.CY Pub Date : 2020-03-25
    Kashyap Thimmaraju; Julian Fietkau; Fatemeh Ganji

    In this paper we describe our experience in designing and evaluating our graduate level computer security seminar course. In particular, our seminar is designed with two goals in mind. First, to instil critical thinking by teaching graduate students how to read, review and present scientific literature. Second, to learn about the state-of-the-art in computer security and privacy research by reviewing

    更新日期:2020-03-27
  • Integrating Physiological Time Series and Clinical Notes with Deep Learning for Improved ICU Mortality Prediction
    arXiv.cs.CY Pub Date : 2020-03-24
    Satya Narayan Shukla; Benjamin M. Marlin

    Intensive Care Unit Electronic Health Records (ICU EHRs) store multimodal data about patients including clinical notes, sparse and irregularly sampled physiological time series, lab results, and more. To date, most methods designed to learn predictive models from ICU EHR data have focused on a single modality. In this paper, we leverage the recently proposed interpolation-prediction deep learning architecture(Shukla

    更新日期:2020-03-26
  • Large-scale network analysis reveals cheating spreads through victimization and observation
    arXiv.cs.CY Pub Date : 2020-03-24
    Ji Eun Kim; Milena Tsvetkova

    Antisocial behavior such as negative gossip, cheating, or bullying can be contagious, spreading from individual to individual and rippling through social networks. Previous experimental research has suggested that individuals who either experience or observe antisocial behavior become more likely to behave antisocially. Here, we distinguish between victimization and observation using an observational

    更新日期:2020-03-26
  • AI loyalty: A New Paradigm for Aligning Stakeholder Interests
    arXiv.cs.CY Pub Date : 2020-03-24
    Anthony Aguirre; Gaia Dempsey; Harry Surden; Peter B. Reiner

    When we consult with a doctor, lawyer, or financial advisor, we generally assume that they are acting in our best interests. But what should we assume when it is an artificial intelligence (AI) system that is acting on our behalf? Early examples of AI assistants like Alexa, Siri, Google, and Cortana already serve as a key interface between consumers and information on the web, and users routinely rely

    更新日期:2020-03-26
  • What is the people posting about symptoms related to Coronavirus in Bogota, Colombia?
    arXiv.cs.CY Pub Date : 2020-03-25
    Josimar E. Chire Saire; Roberto C. Navarro

    During the last months, there is an increasing alarm about a new mutation of coronavirus, covid-19 coined by World Health Organization(WHO) with an impact in many areas: economy, health, politics and others. This situation was declared a pandemic by WHO, because of the fast expansion over many countries. At the same time, people is using Social Networks to express what they think, feel or experiment

    更新日期:2020-03-26
  • Artificial Intelligence for EU Decision-Making. Effects on Citizens Perceptions of Input, Throughput and Output Legitimacy
    arXiv.cs.CY Pub Date : 2020-03-25
    Christopher Starke; Marco Luenich

    A lack of political legitimacy undermines the ability of the European Union to resolve major crises and threatens the stability of the system as a whole. By integrating digital data into political processes, the EU seeks to base decision-making increasingly on sound empirical evidence. In particular, artificial intelligence systems have the potential to increase political legitimacy by identifying

    更新日期:2020-03-26
  • Mapping the Landscape of Artificial Intelligence Applications against COVID-19
    arXiv.cs.CY Pub Date : 2020-03-25
    Joseph BullockSasha; AlexandraSasha; Luccioni; Katherine Hoffmann Pham; Cynthia Sin Nga Lam; Miguel Luengo-Oroz

    COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, with over 294,000 cases as of March 22nd 2020. In this review, we present an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence, to tackle many aspects of the COVID-19 crisis at different scales including molecular, medical and epidemiological

    更新日期:2020-03-26
  • Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings
    arXiv.cs.CY Pub Date : 2020-03-11
    Haoran Zhang; Amy X. Lu; Mohamed Abdalla; Matthew McDermott; Marzyeh Ghassemi

    In this work, we examine the extent to which embeddings may encode marginalized populations differently, and how this may lead to a perpetuation of biases and worsened performance on clinical tasks. We pretrain deep embedding models (BERT) on medical notes from the MIMIC-III hospital dataset, and quantify potential disparities using two approaches. First, we identify dangerous latent relationships

    更新日期:2020-03-26
  • Locally Interpretable Predictions of Parkinson's Disease Progression
    arXiv.cs.CY Pub Date : 2020-03-20
    Qiaomei Li; Rachel Cummings; Yonatan Mintz

    In precision medicine, machine learning techniques have been commonly proposed to aid physicians in early screening of chronic diseases such as Parkinson's Disease. These automated screening procedures should be interpretable by a clinician who must explain the decision-making process to patients for informed consent. However, the methods which typically achieve the highest level of accuracy given

    更新日期:2020-03-24
  • Hazard recognition in an immersive virtual environment: Framework for the simultaneous analysis of visual search and EEG patterns
    arXiv.cs.CY Pub Date : 2020-03-14
    Mojtaba Noghabaei; Kevin Han

    Unmanaged hazards in dangerous construction environments proved to be one of the main sources of injuries and accidents. Hazard recognition is crucial to achieve effective safety management and reduce injuries and fatalities in hazardous job sites. Still, there has been lack of effort that can efficiently assist workers in improving their hazard recognition skills. This study presents virtual safety

    更新日期:2020-03-24
  • Novel Coronavirus COVID-19 Strike on Arab Countries and Territories: A Situation Report I
    arXiv.cs.CY Pub Date : 2020-03-20
    Omar Reyad

    The novel Coronavirus (COVID-19) is an infectious disease caused by a new virus called COVID-19 or 2019-nCoV that first identified in Wuhan, China. The disease causes respiratory illness (such as the flu) with other symptoms such as a cough, fever, and in more severe cases, difficulty breathing. This new Coronavirus seems to be very infectious and has spread quickly and globally. In this work, information

    更新日期:2020-03-24
  • Identifying At-Risk K-12 Students in Multimodal Online Environments: A Machine Learning Approach
    arXiv.cs.CY Pub Date : 2020-03-21
    Hang Li; Wenbiao Ding; Songfan Yang; Zitao Liu

    With the rapid emergence of K-12 online learning platforms, a new era of education has been opened up. By offering more affordable and personalized courses compared to in-person classrooms, K-12 online tutoring is pushing the boundaries of education to the general public. It is crucial to have a dropout warning framework to preemptively identify K-12 students who are at risk of dropping out of the

    更新日期:2020-03-24
  • Automatic scoring of apnea and hypopnea events using blood oxygen saturation signals
    arXiv.cs.CY Pub Date : 2020-03-22
    R. E. Rolon; I. E. Gareis; L. E. Di Persia; R. D. Spies; H. L. Rufiner

    The obstructive sleep apnea-hypopnea (OSAH) syndrome is a very common and frequently undiagnosed sleep disorder. It is characterized by repeated events of partial (hypopnea) or total (apnea) obstruction of the upper airway while sleeping. This study makes use of a previously developed method called DAS-KSVD for multiclass structured dictionary learning to automatically detect individual events of apnea

    更新日期:2020-03-24
  • Design Multimedia Expert Diagnosing Diseases System Using Fuzzy Logic (MEDDSFL)
    arXiv.cs.CY Pub Date : 2020-03-22
    Mohammed Salah Ibrahim; Doaa Waleed Al-Dulaimee

    In this paper we designed an efficient expert system to diagnose diseases for human beings. The system depended on several clinical features for different diseases which will be used as knowledge base for this system. We used fuzzy logic system which is one of the most expert systems techniques that used in building knowledge base of expert systems. Fuzzy logic will be used to inference the results

    更新日期:2020-03-24
  • Analysis and Prediction of Pedestrian Crosswalk Behavior during Automated Vehicle Interactions
    arXiv.cs.CY Pub Date : 2020-03-22
    Suresh Kumaar Jayaraman; Dawn M. Tilbury; X. Jessie Yang; Anuj K. Pradhan; Lionel P. Robert Jr

    For safe navigation around pedestrians, automated vehicles (AVs) need to plan their motion by accurately predicting pedestrians trajectories over long time horizons. Current approaches to AV motion planning around crosswalks predict only for short time horizons (1-2 s) and are based on data from pedestrian interactions with human-driven vehicles (HDVs). In this paper, we develop a hybrid systems model

    更新日期:2020-03-24
  • Efficient Behavior-aware Control of Automated Vehicles at Crosswalks using Minimal Information Pedestrian Prediction Model
    arXiv.cs.CY Pub Date : 2020-03-22
    Suresh Kumaar Jayaraman; Lionel P. Robert Jr.; Xi Jessie Yang; Anuj K. Pradhan; Dawn M. Tilbury

    For automated vehicles (AVs) to reliably navigate through crosswalks, they need to understand pedestrians crossing behaviors. Simple and reliable pedestrian behavior models aid in real-time AV control by allowing the AVs to predict future pedestrian behaviors. In this paper, we present a Behavior aware Model Predictive Controller (B-MPC) for AVs that incorporates long-term predictions of pedestrian

    更新日期:2020-03-24
  • Proximity: a recipe to break the outbreak
    arXiv.cs.CY Pub Date : 2020-03-23
    Marco Faggian; Michele Urbani; Luca Zanotto

    We present a mobile app solution to help the containment of an epidemic outbreak by keeping track of possible infections in the incubation period. We consider the particular case of an infection which primarily spreads among people through proximal contact, via respiratory droplets. This smartphone application will work offline and will be able to detect other devices in close proximity and list all

    更新日期:2020-03-24
  • From Bit To Bedside: A Practical Framework For Artificial Intelligence Product Development In Healthcare
    arXiv.cs.CY Pub Date : 2020-03-23
    David Higgins; Vince I. Madai

    Artificial Intelligence (AI) in healthcare holds great potential to expand access to high-quality medical care, whilst reducing overall systemic costs. Despite hitting the headlines regularly and many publications of proofs-of-concept, certified products are failing to breakthrough to the clinic. AI in healthcare is a multi-party process with deep knowledge required in multiple individual domains.

    更新日期:2020-03-24
  • Entropy as a measure of attractiveness and socioeconomic complexity in Rio de Janeiro metropolitan area
    arXiv.cs.CY Pub Date : 2020-03-23
    Maxime Lenormand; Horacio Samaniego; Julio C. Chaves; Vinicius F. Vieira; Moacyr A. H. B. da Silva; Alexandre G. Evsukoff

    Defining and measuring spatial inequalities across the urban environment remains a complex and elusive task that has been facilitated by the increasing availability of large geolocated databases. In this study, we rely on a mobile phone dataset and an entropy-based metric to measure the attractiveness of a location in the Rio de Janeiro Metropolitan Area (Brazil) as the diversity of visitors' location

    更新日期:2020-03-24
  • Transforming Commercial Contracts through Computable Contracting
    arXiv.cs.CY Pub Date : 2020-03-23
    John Cummins; Christopher Clack

    Contracts are an essential and fundamental component of commerce and society, serving to clarify agreement between multiple parties. While digital technologies have helped to automate many activities associated with contracting, the contracts themselves continue, in the main, to be in the form of unstructured, natural-language text. This limits the scope for improvements in productivity and automation

    更新日期:2020-03-24
  • Ethics in the digital era
    arXiv.cs.CY Pub Date : 2020-03-14
    David Pastor-Escuredo

    Ethics is an ancient matter for human kind, from the origin of civilizations ethics have been related with the most relevant human concerns and determined human behavior. Ethics was initially related to religion, politics and philosophy to then be fragmented into specific disciplines and communities of practice. The undergoing digital revolution enabled by Artificial Intelligence and Big Data are bringing

    更新日期:2020-03-24
  • NELA-GT-2019: A Large Multi-Labelled News Dataset for The Study of Misinformation in News Articles
    arXiv.cs.CY Pub Date : 2020-03-18
    Maurício Gruppi; Benjamin D. Horne; Sibel Adalı

    In this paper, we present an updated version of the NELA-GT-2018 dataset (N{\o}rregaard, Horne, and Adal{\i} 2019), entitled NELA-GT-2019. NELA-GT-2019 contains 1.12M news articles from 260 sources collected between January 1st 2019 and December 31st 2019. Just as with NELA-GT-2018, these sources come from a wide range of mainstream news sources and alternative news sources. Included with the dataset

    更新日期:2020-03-20
  • TILES-2018: A longitudinal physiologic and behavioral data set of hospital workers
    arXiv.cs.CY Pub Date : 2020-03-18
    Karel Mundnich; Brandon M. Booth; Michelle L'Hommedieu; Tiantian Feng; Benjamin Girault; Justin L'Hommedieu; Mackenzie Wildman; Sophia Skaaden; Amrutha Nadarajan; Jennifer L. Villatte; Tiago H. Falk; Kristina Lerman; Emilio Ferrara; Shrikanth Narayanan

    We present a novel longitudinal multimodal corpus of physiological and behavioral data collected from direct clinical providers in a hospital workplace. We designed the study to investigate the use of off-the-shelf wearable and environmental sensors to understand individual-specific constructs such as job performance, interpersonal interaction, and well-being of hospital workers over time in their

    更新日期:2020-03-20
  • Empirical Characterization of Mobility of Multi-Device Internet Users
    arXiv.cs.CY Pub Date : 2020-03-18
    Amee Trivedi; Jeremy Gummeson; Prashant Shenoy

    Understanding the mobility of humans and their devices is a fundamental problem in mobile computing. While there has been much work on empirical analysis of human mobility using mobile device data, prior work has largely assumed devices to be independent and has not considered the implications of modern Internet users owning multiple mobile devices that exhibit correlated mobility patterns. Also, prior

    更新日期:2020-03-20
  • Super Low Resolution RF Powered Accelerometers for Alerting on Hospitalized Patient Bed Exits
    arXiv.cs.CY Pub Date : 2020-03-19
    Michael Chesser; Asangi Jayatilaka; Renuka Visvanathan; Christophe Fumeaux; Alanson Sample; Damith C. Ranasinghe

    Falls have serious consequences and are prevalent in acute hospitals and nursing homes caring for older people. Most falls occur in bedrooms and near the bed. Technological interventions to mitigate the risk of falling aim to automatically monitor bed-exit events and subsequently alert healthcare personnel to provide timely supervisions. We observe that frequency-domain information related to patient

    更新日期:2020-03-20
  • Apps Gone Rogue: Maintaining Personal Privacy in an Epidemic
    arXiv.cs.CY Pub Date : 2020-03-19
    Ramesh Raskar; Isabel Schunemann; Rachel Barbar; Kristen Vilcans; Jim Gray; Praneeth Vepakomma; Suraj Kapa; Andrea Nuzzo; Rajiv Gupta; Alex Berke; Dazza Greenwood; Christian Keegan; Shriank Kanaparti; Robson Beaudry; David Stansbury; Beatriz Botero Arcila; Rishank Kanaparti; Vitor Pamplona; Francesco M Benedetti; Alina Clough; Riddhiman Das; Kaushal Jain; Khahlil Louisy; Greg Nadeau; Vitor Pamplona;

    Containment, the key strategy in quickly halting an epidemic, requires rapid identification and quarantine of the infected individuals, determination of whom they have had close contact with in the previous days and weeks, and decontamination of locations the infected individual has visited. Achieving containment demands accurate and timely collection of the infected individual's location and contact

    更新日期:2020-03-20
  • Conducting Privacy-Sensitive Surveys: A Case Study of Civil Society Organizations
    arXiv.cs.CY Pub Date : 2020-03-19
    Nikita Samarin; Alisa Frik; Sean Brooks; Coye Cheshire; Serge Egelman

    Compared to other organizations, civil society organizations (CSOs) often operate in elevated-risk contexts, and attacks against them carry much greater ramifications, including threats to freedom of expression, liberty, and life. We aim to capture the factors that affect the attitudes and intentions of CSO employees to engage in security and privacy behaviors by using a survey-based study to collect

    更新日期:2020-03-20
  • Cardiovascular risk and work stress in biomedical researchers in China: An observational, big data study protocol
    arXiv.cs.CY Pub Date : 2020-03-19
    Fang Zhu; Qian Zhang; Hao Chen; Guocheng Shi; Chen Wen; Zhongqun Zhu; Huiwen Chen

    Introduction: Internet technologies could strengthen data collection and integration and have been used extensively in public health research. It is necessary to apply this technology to further investigate the behaviour and health of biomedical researchers. A browser-based extension was developed by researchers and clinicians to promote the collection and analysis of researchers' behavioural and psychological

    更新日期:2020-03-20
  • Text-mining forma mentis networks reconstruct public perception of the STEM gender gap in social media
    arXiv.cs.CY Pub Date : 2020-03-18
    Massimo Stella

    Mindset reconstruction maps how individuals structure and perceive knowledge, a map unfolded here by investigating language and its cognitive reflection in the human mind, i.e. the mental lexicon. Textual forma mentis networks (TFMN) are glass boxes introduced for extracting, representing and understanding mindsets' structure, in Latin "forma mentis", from textual data. Combining network science, psycholinguistics

    更新日期:2020-03-20
  • Fairness in Deep Learning: A Computational Perspective
    arXiv.cs.CY Pub Date : 2019-08-23
    Mengnan Du; Fan Yang; Na Zou; Xia Hu

    Deep learning is increasingly being used in high-stake decision making applications that affect individual lives. However, deep learning models might exhibit algorithmic discrimination behaviors with respect to protected groups, potentially posing negative impacts on individuals and society. Therefore, fairness in deep learning has attracted tremendous attention recently. We provide a review covering

    更新日期:2020-03-20
  • An Overview and Case Study of the Clinical AI Model Development Life Cycle for Healthcare Systems
    arXiv.cs.CY Pub Date : 2020-03-02
    Charles Lu; Julia Strout; Romane Gauriau; Brad Wright; Fabiola Bezerra De Carvalho Marcruz; Varun Buch; Katherine Andriole

    Healthcare is one of the most promising areas for machine learning models to make a positive impact. However, successful adoption of AI-based systems in healthcare depends on engaging and educating stakeholders from diverse backgrounds about the development process of AI models. We present a broadly accessible overview of the development life cycle of clinical AI models that is general enough to be

    更新日期:2020-03-20
  • Generating Electronic Health Records with Multiple Data Types and Constraints
    arXiv.cs.CY Pub Date : 2020-03-17
    Chao Yan; Ziqi Zhang; Steve Nyemba; Bradley A. Malin

    Sharing electronic health records (EHRs) on a large scale may lead to privacy intrusions. Recent research has shown that risks may be mitigated by simulating EHRs through generative adversarial network (GAN) frameworks. Yet the methods developed to date are limited because they 1) focus on generating data of a single type (e.g., diagnosis codes), neglecting other data types (e.g., demographics, procedures

    更新日期:2020-03-19
  • Towards Peer-to-Peer Energy Market: an Overview
    arXiv.cs.CY Pub Date : 2020-03-02
    Ramon Christen; Luca Mazzola; Alexander Denzler

    This paper provides an overview of the current status of the energy market, with respect to the increasing number of decentralised prosumer. After outlining the limitations imposed by the status quo, a possible multi-layered architecture of a Peer-to-Peer (P2P) energy market is introduced. The fundamental aspects of local production and local consumption as part of a microgrid are discussed. Changes

    更新日期:2020-03-19
  • Forecasting Crime Using ARIMA Model
    arXiv.cs.CY Pub Date : 2020-03-18
    Khawar Islam; Akhter Raza

    Data mining is the process in which we extract the different patterns and useful Information from large dataset. According to London police, crimes are immediately increases from beginning of 2017 in different borough of London. No useful information is available for prevent crime on future basis. We forecasts crime rates in London borough by extracting large dataset of crime in London and predicted

    更新日期:2020-03-19
  • The Future of Digital Health with Federated Learning
    arXiv.cs.CY Pub Date : 2020-03-18
    Nicola Rieke; Jonny Hancox; Wenqi Li; Fausto Milletari; Holger Roth; Shadi Albarqouni; Spyridon Bakas; Mathieu N. Galtier; Bennett Landman; Klaus Maier-Hein; Sebastien Ourselin; Micah Sheller; Ronald M. Summers; Andrew Trask; Daguang Xu; Maximilian Baust; M. Jorge Cardoso

    Data-driven Machine Learning has emerged as a promising approach for building accurate and robust statistical models from medical data, which is collected in huge volumes by modern healthcare systems. Existing medical data is not fully exploited by ML primarily because it sits in data silos and privacy concerns restrict access to this data. However, without access to sufficient data, ML will be prevented

    更新日期:2020-03-19
  • How social feedback processing in the brain shapes collective opinion processes in the era of social media
    arXiv.cs.CY Pub Date : 2020-03-18
    Sven Banisch; Felix Gaisbauer; Eckehard Olbrich

    What are the mechanisms by which groups with certain opinions gain public voice and force others holding a different view into silence? And how does social media play into this? Drawing on recent neuro-scientific insights into the processing of social feedback, we develop a theoretical model that allows to address these questions. The model captures phenomena described by spiral of silence theory of

    更新日期:2020-03-19
  • Designing Tools for Semi-Automated Detection of Machine Learning Biases: An Interview Study
    arXiv.cs.CY Pub Date : 2020-03-13
    Po-Ming Law; Sana Malik; Fan Du; Moumita Sinha

    Machine learning models often make predictions that bias against certain subgroups of input data. When undetected, machine learning biases can constitute significant financial and ethical implications. Semi-automated tools that involve humans in the loop could facilitate bias detection. Yet, little is known about the considerations involved in their design. In this paper, we report on an interview

    更新日期:2020-03-19
  • Harnessing Explanations to Bridge AI and Humans
    arXiv.cs.CY Pub Date : 2020-03-16
    Vivian Lai; Samuel Carton; Chenhao Tan

    Machine learning models are increasingly integrated into societally critical applications such as recidivism prediction and medical diagnosis, thanks to their superior predictive power. In these applications, however, full automation is often not desired due to ethical and legal concerns. The research community has thus ventured into developing interpretable methods that explain machine predictions

    更新日期:2020-03-18
  • FakeYou! -- A Gamified Approach for Building and Evaluating Resilience Against Fake News
    arXiv.cs.CY Pub Date : 2020-03-17
    Lena Clever; Dennis Assenmacher; Kilian Müller; Moritz Vinzent Seiler; Dennis M. Riehle; Mike Preuss; Christian Grimme

    Nowadays fake news are heavily discussed in public and political debates. Even though the phenomenon of intended false information is rather old, misinformation reaches a new level with the rise of the internet and participatory platforms. Due to Facebook and Co., purposeful false information - often called fake news - can be easily spread by everyone. Because of a high data volatility and variety

    更新日期:2020-03-18
  • Fair inference on error-prone outcomes
    arXiv.cs.CY Pub Date : 2020-03-17
    Laura Boeschoten; Erik-Jan van Kesteren; Ayoub Bagheri; Daniel L. Oberski

    Fair inference in supervised learning is an important and active area of research, yielding a range of useful methods to assess and account for fairness criteria when predicting ground truth targets. As shown in recent work, however, when target labels are error-prone, potential prediction unfairness can arise from measurement error. In this paper, we show that, when an error-prone proxy target is

    更新日期:2020-03-18
  • Chemotaxis and Quorum Sensing inspired Device Interaction supporting Social Networking
    arXiv.cs.CY Pub Date : 2020-03-06
    Sasitharan Balasubramaniam; Dmitri Botvich; Tao Gu; William Donnelly

    Conference and social events provides an opportunity for people to interact and develop formal contacts with various groups of individuals. In this paper, we propose an efficient interaction mechanism in a pervasive computing environment that provide recommendation to users of suitable locations within a conference or expo hall to meet and interact with individuals of similar interests. The proposed

    更新日期:2020-03-18
  • Urban Traffic Monitoring and Modeling System: An IoT Solution for Enhancing Road Safety
    arXiv.cs.CY Pub Date : 2020-03-05
    Rateb Jabbar; Mohammed Shinoy; Mohamed Kharbeche; Khalifa Al-Khalifa; Moez Krichenz; Kamel Barkaouiy

    Qatar expects more than a million visitors during the 2022 World Cup, which will pose significant challenges. The high number of people will likely cause a rise in road traffic congestion, vehicle crashes, injuries and deaths. To tackle this problem, Naturalistic Driver Behavior can be utilised which will collect and analyze data to estimate the current Qatar traffic system, including traffic data

    更新日期:2020-03-18
  • Risk Management Practices in Information Security: Exploring the Status Quo in the DACH Region
    arXiv.cs.CY Pub Date : 2020-03-04
    Michael Brunner; Clemens Sauerwein; Michael Felderer; Ruth Breu

    Information security management aims at ensuring proper protection of information values and information processing systems (i.e. assets). Information security risk management techniques are incorporated to deal with threats and vulnerabilities that impose risks to information security properties of these assets. This paper investigates the current state of risk management practices being used in information

    更新日期:2020-03-18
  • Business (mis)Use Cases of Generative AI
    arXiv.cs.CY Pub Date : 2020-03-02
    Stephanie Houde; Vera Liao; Jacquelyn Martino; Michael Muller; David Piorkowski; John Richards; Justin Weisz; Yunfeng Zhang

    Generative AI is a class of machine learning technology that learns to generate new data from training data. While deep fakes and media-and art-related generative AI breakthroughs have recently caught people's attention and imagination, the overall area is in its infancy for business use. Further, little is known about generative AI's potential for malicious misuse at large scale. Using co-creation

    更新日期:2020-03-18
  • The Data Science Fire Next Time: Innovative strategies for mentoring in data science
    arXiv.cs.CY Pub Date : 2020-03-01
    Latifa Jackson; Heriberto Acosta Maestre

    As data mining research and applications continue to expand in to a variety of fields such as medicine, finance, security, etc., the need for talented and diverse individuals is clearly felt. This is particularly the case as Big Data initiatives have taken off in the federal, private and academic sectors, providing a wealth of opportunities, nationally and internationally. The Broadening Participation

    更新日期:2020-03-18
  • Who Wins the Game of Thrones? How Sentiments Improve the Prediction of Candidate Choice
    arXiv.cs.CY Pub Date : 2020-02-29
    Chaehan So

    This paper analyzes how candidate choice prediction improves by different psychological predictors. To investigate this question, it collected an original survey dataset featuring the popular TV series "Game of Thrones". The respondents answered which character they anticipated to win in the final episode of the series, and explained their choice of the final candidate in free text from which sentiments

    更新日期:2020-03-18
  • Supporting Early and Scalable Discovery of Disinformation Websites
    arXiv.cs.CY Pub Date : 2020-02-28
    Austin Hounsel; Jordan Holland; Ben Kaiser; Kevin Borgolte; Nick Feamster; Jonathan Mayer

    Online disinformation is a serious and growing sociotechnical problem that threatens the integrity of public discourse, democratic governance, and commerce. The internet has made it easier than ever to spread false information, and academic research is just beginning to comprehend the consequences. In response to this growing problem, online services have established processes to counter disinformation

    更新日期:2020-03-18
  • Augmented reality as a tool for open science platform by research collaboration in virtual teams
    arXiv.cs.CY Pub Date : 2020-02-28
    Mariya P. Shyshkina; Maiia V. Marienko

    The provision of open science is defined as a general policy aimed at overcoming the barriers that hinder the implementation of the European Research Area (ERA). An open science foundation seeks to capture all the elements needed for the functioning of ERA: research data, scientific instruments, ICT services (connections, calculations, platforms, and specific studies such as portals). Managing shared

    更新日期:2020-03-18
  • Data-Driven Metadata Tagging for Building Automation Systems: A Unified Architecture
    arXiv.cs.CY Pub Date : 2020-02-27
    Sakshi Mishra; Andrew Glaws; Dylan Cutler; Stephen Frank; Muhammad Azam; Farzam Mohammadi; Jean-Simon Venne

    This article presents a Unified Architecture for automated point tagging of Building Automation System data, based on a combination of data-driven approaches. Advanced energy analytics applications-including fault detection and diagnostics and supervisory control-have emerged as a significant opportunity for improving the performance of our built environment. Effective application of these analytics

    更新日期:2020-03-18
  • Inferring Nighttime Satellite Imagery from Human Mobility
    arXiv.cs.CY Pub Date : 2020-02-28
    Brian Dickinson; Gourab Ghoshal; Xerxes Dotiwalla; Adam Sadilek; Henry Kautz

    Nighttime lights satellite imagery has been used for decades as a uniform, global source of data for studying a wide range of socioeconomic factors. Recently, another more terrestrial source is producing data with similarly uniform global coverage: anonymous and aggregated smart phone location. This data, which measures the movement patterns of people and populations rather than the light they produce

    更新日期:2020-03-18
  • Flexible and Context-Specific AI Explainability: A Multidisciplinary Approach
    arXiv.cs.CY Pub Date : 2020-03-13
    Valérie BeaudouinSES; Isabelle BlochIMAGES; David BounieIP Paris, ECOGE, SES; Stéphan ClémençonLPMA; Florence d'Alché-BucDIVA; James EaganDIVA; Winston MaxwellIRMAR; Pavlo MozharovskyiIRMAR; Jayneel Parekh

    The recent enthusiasm for artificial intelligence (AI) is due principally to advances in deep learning. Deep learning methods are remarkably accurate, but also opaque, which limits their potential use in safety-critical applications. To achieve trust and accountability, designers and operators of machine learning algorithms must be able to explain the inner workings, the results and the causes of failures

    更新日期:2020-03-18
  • Can Celebrities Burst Your Bubble?
    arXiv.cs.CY Pub Date : 2020-03-15
    Tuğrulcan Elmas; Kristina Hardi; Rebekah Overdorf; Karl Aberer

    Polarization is a growing, global problem. As such, many social media based solutions have been proposed in order to reduce it. In this study, we propose a new solution that recommends topics to celebrities to encourage them to join a polarized debate and increase exposure to contrarian content - bursting the filter bubble. Using a state-of-the art model that quantifies the degree of polarization,

    更新日期:2020-03-18
  • Socratrees: Exploring the Design of Argument Technology for Layman Users
    arXiv.cs.CY Pub Date : 2018-12-11
    Steven Jeuris

    Terms like 'misinformation', 'fake news', and 'echo chambers' permeate current discussions on the state of the Internet. We believe a lack of technological support to evaluate, contest, and reason about information online---as opposed to merely disseminating it---lies at the root of these problems. Several argument technologies support such functionality, but have seen limited use outside of niche

    更新日期:2020-03-18
  • Tracing patients' PLOD with mobile phones: Mitigation of epidemic risks through patients' locational open data
    arXiv.cs.CY Pub Date : 2020-03-13
    Ikki Ohmukai; Yasunori Yamamoto; Maori Ito; Takashi Okumura

    In the cases when public health authorities confirm a patient with highly contagious disease, they release the summaries about patient locations and travel information. However, due to privacy concerns, these releases do not include the detailed data and typically comprise the information only about commercial facilities and public transportation used by the patients. We addressed this problem and

    更新日期:2020-03-16
  • Large-Scale Educational Question Analysis with Partial Variational Auto-encoders
    arXiv.cs.CY Pub Date : 2020-03-12
    Zichao Wang; Sebastian Tschiatschek; Simon Woodhead; Jose Miguel Hernandez-Lobato; Simon Peyton Jones; Cheng Zhang

    Online education platforms enable teachers to share a large number of educational resources such as questions to form exercises and quizzes for students. With large volumes of such crowd-sourced questions, quantifying the properties of these questions in crowd-sourced online education platforms is of great importance to enable both teachers and students to find high-quality and suitable resources.

    更新日期:2020-03-16
  • Tendrils of Crime: Visualizing the Diffusion of Stolen Bitcoins
    arXiv.cs.CY Pub Date : 2019-01-07
    Mansoor Ahmed-Rengers; Ilia Shumailov; Ross Anderson

    The first six months of 2018 saw cryptocurrency thefts of $761 million, and the technology is also the latest and greatest tool for money laundering. This increase in crime has caused both researchers and law enforcement to look for ways to trace criminal proceeds. Although tracing algorithms have improved recently, they still yield an enormous amount of data of which very few datapoints are relevant

    更新日期:2020-03-16
  • A Computational Investigation on Denominalization
    arXiv.cs.CY Pub Date : 2020-02-13
    Zahra Shekarchi; Yang Xu

    Language has been a dynamic system and word meanings always have been changed over times. Every time a novel concept or sense is introduced, we need to assign it a word to express it. Also, some changes have happened because the result of a change can be more desirable for humans, or cognitively easier to be used by humans. Finding the patterns of these changes is interesting and can reveal some facts

    更新日期:2020-03-12
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