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  • An Enhanced Geo Location Technique for Social Network Communication System
    arXiv.cs.CY Pub Date : 2020-09-05
    Odikwa Henry; Ifeanyi-Reuben Nkechi; Thom-Manuel Osaki Miller

    Social networks have become very popular in recent years because of the increasing large number and affordability of internet enabled gadgets such as personal computers, mobile devices and internet tablets. It has been observed that the tempo of fraud in social media these days is over alarming most especially in Nigeria. As a result of this, there is need to fortify the social network services in

    更新日期:2020-09-23
  • Mosques Smart Domes System using Machine Learning Algorithms
    arXiv.cs.CY Pub Date : 2020-08-30
    Mohammad Awis Al Lababede; Anas H. Blasi; Mohammed A. Alsuwaiket

    Millions of mosques around the world are suffering some problems such as ventilation and difficulty getting rid of bacteria, especially in rush hours where congestion in mosques leads to air pollution and spread of bacteria, in addition to unpleasant odors and to a state of discomfort during the pray times, where in most mosques there are no enough windows to ventilate the mosque well. This paper aims

    更新日期:2020-09-23
  • Ethical Machine Learning in Health
    arXiv.cs.CY Pub Date : 2020-09-22
    Irene Y. Chen; Emma Pierson; Sherri Rose; Shalmali Joshi; Kadija Ferryman; Marzyeh Ghassemi

    The use of machine learning (ML) in health care raises numerous ethical concerns, especially as models can amplify existing health inequities. Here, we outline ethical considerations for equitable ML in the advancement of health care. Specifically, we frame ethics of ML in health care through the lens of social justice. We describe ongoing efforts and outline challenges in a proposed pipeline of ethical

    更新日期:2020-09-23
  • Football and externalities: Using mathematical modelling to predict the changing fortunes of Newcastle United
    arXiv.cs.CY Pub Date : 2020-09-22
    Vishist Srivastava; Prashant Yadav; Ajuni Singh

    The Public Investment Fund (PIF), is Saudi Arabia's sovereign wealth fund. It is one of the world's largest sovereign wealth funds, with an estimated net capital of $382 billion. It was established to invest funds on behalf of the Government of Saudi Arabia. Saudi Arabia is aiming to transfer the PIF from a mere local authority to the world's largest sovereign fund. Thus, PIF is working to manage $400

    更新日期:2020-09-23
  • A narrowing of AI research?
    arXiv.cs.CY Pub Date : 2020-09-22
    Joel Klinger; Juan Mateos-Garcia; Konstantinos Stathoulopoulos

    Artificial Intelligence (AI) is being hailed as the latest example of a General Purpose Technology that could transform productivity and help tackle important societal challenges. This outcome is however not guaranteed: a myopic focus on short-term benefits could lock AI into technologies that turn out to be sub-optimal in the longer-run. Recent controversies about the dominance of deep learning methods

    更新日期:2020-09-23
  • Usage Patterns of Privacy-Enhancing Technologies
    arXiv.cs.CY Pub Date : 2020-09-22
    Kovila P. L. Coopamootoo

    The steady reports of privacy invasions online paints a picture of the Internet growing into a more dangerous place. This is supported by reports of the potential scale for online harms facilitated by the mass deployment of online technology and the data-intensive web. While Internet users often express concern about privacy, some report taking actions to protect their privacy online. We investigate

    更新日期:2020-09-23
  • Designing AI Learning Experiences for K-12: Emerging Works, Future Opportunities and a Design Framework
    arXiv.cs.CY Pub Date : 2020-09-22
    Xiaofei Zhou; Jessica Van Brummelen; Phoebe Lin

    Artificial intelligence (AI) literacy is a rapidly growing research area and a critical addition to K-12 education. However, support for designing tools and curriculum to teach K-12 AI literacy is still limited. There is a need for additional interdisciplinary human-computer interaction and education research investigating (1) how general AI literacy is currently implemented in learning experiences

    更新日期:2020-09-23
  • Online geolocalized emotion across US cities during the COVID crisis: Universality, policy response, and connection with local mobility
    arXiv.cs.CY Pub Date : 2020-09-22
    Shihui Feng; Alec Kirkley

    As the COVID-19 pandemic began to sweep across the US it elicited a wide spectrum of responses, both online and offline, across the population. To aid the development of effective spatially targeted interventions in the midst of this turmoil, it is important to understand the geolocalization of these online emotional responses, as well as their association with offline behavioral responses. Here, we

    更新日期:2020-09-23
  • iWash: A Smartwatch Handwashing Quality Assessment and Reminder System with Real-time Feedback in the Context of Infectious Disease
    arXiv.cs.CY Pub Date : 2020-09-22
    Sirat Samyoun; Sudipta Saha Shubha; Md Abu Sayeed Mondol; John A. Stankovic

    Washing hands properly and frequently is the simplest and most cost-effective interventions to prevent the spread of infectious diseases. People are often ignorant about proper handwashing in different situations and do not know if they wash hands properly. Smartwatches are found to be effective for assessing the quality of handwashing. However, the existing smartwatch based systems are not comprehensive

    更新日期:2020-09-23
  • Semantic Workflows and Machine Learning for the Assessment of Carbon Storage by Urban Trees
    arXiv.cs.CY Pub Date : 2020-09-22
    Juan Carrillo; Daniel Garijo; Mark Crowley; Rober Carrillo; Yolanda Gil; Katherine Borda

    Climate science is critical for understanding both the causes and consequences of changes in global temperatures and has become imperative for decisive policy-making. However, climate science studies commonly require addressing complex interoperability issues between data, software, and experimental approaches from multiple fields. Scientific workflow systems provide unparalleled advantages to address

    更新日期:2020-09-23
  • Dark Patterns and the Legal Requirements of Consent Banners: An Interaction Criticism Perspective
    arXiv.cs.CY Pub Date : 2020-09-21
    Colin M. Gray; Cristiana Santos; Nataliia Bielova; Michael Toth; Damian Clifford

    User engagement with data privacy and security through consent banners has become a ubiquitous part of interacting with internet services. While previous work has addressed consent banners from either interaction design, legal, and ethics-focused perspectives, little research addresses the connections among multiple disciplinary approaches, including tensions and opportunities that transcend disciplinary

    更新日期:2020-09-23
  • Proposal of a Novel Bug Bounty Implementation Using Gamification
    arXiv.cs.CY Pub Date : 2020-09-21
    Jamie O'Hare; Lynsay A. Shepherd

    Despite significant popularity, the bug bounty process has remained broadly unchanged since its inception, with limited implementation of gamification aspects. Existing literature recognises that current methods generate intensive resource demands, and can encounter issues impacting program effectiveness. This paper proposes a novel bug bounty process aiming to alleviate resource demands and mitigate

    更新日期:2020-09-23
  • Measuring justice in machine learning
    arXiv.cs.CY Pub Date : 2020-09-21
    Alan Lundgard

    How can we build more just machine learning systems? To answer this question, we need to know both what justice is and how to tell whether one system is more or less just than another. That is, we need both a definition and a measure of justice. Theories of distributive justice hold that justice can be measured (in part) in terms of the fair distribution of benefits and burdens across people in society

    更新日期:2020-09-22
  • Synthetic Control, Synthetic Interventions, and COVID-19 spread: Exploring the impact of lockdown measures and herd immunity
    arXiv.cs.CY Pub Date : 2020-09-21
    Niloofar Bayat; Cody Morrin; Yuheng Wang; Vishal Misra

    The synthetic control method is an empirical methodology forcausal inference using observational data. By observing thespread of COVID-19 throughout the world, we analyze the dataon the number of deaths and cases in different regions usingthe power of prediction, counterfactual analysis, and syntheticinterventions of the synthetic control and its extensions. Weobserve that the number of deaths and

    更新日期:2020-09-22
  • A Non-negative Matrix Factorization Based Method for Quantifying Rhythms of Activity and Sleep and Chronotypes Using Mobile Phone Data
    arXiv.cs.CY Pub Date : 2020-09-21
    Talayeh Aledavood; Ilkka Kivimäki; Sune Lehmann; Jari Saramäki

    Human activities follow daily, weekly, and seasonal rhythms. The emergence of these rhythms is related to physiology and natural cycles as well as social constructs. The human body and biological functions undergo near 24-hour rhythms (circadian rhythms). The frequency of these rhythms is more or less similar across people, but its phase is different. In the chronobiology literature, based on the propensity

    更新日期:2020-09-22
  • Detailed Review of Cloud based Mobile application for the stroke patient
    arXiv.cs.CY Pub Date : 2020-09-17
    Balagopal Ramdurai

    In the current years, due to the significant developments in technologies in almost every domain, the standard of living has been improved. Emergence of latest innovations, advanced machinery and equipment especially in the healthcare domain, have simplified the diagonalizing process to a wide extent.

    更新日期:2020-09-22
  • Biases in Data Science Lifecycle
    arXiv.cs.CY Pub Date : 2020-09-10
    Dinh-An Ho; Oya Beyan

    In recent years, data science has become an indispensable part of our society. Over time, we have become reliant on this technology because of its opportunity to gain value and new insights from data in any field - business, socializing, research and society. At the same time, it raises questions about how justified we are in placing our trust in these technologies. There is a risk that such powers

    更新日期:2020-09-22
  • Identifying synergies in private and public transportation
    arXiv.cs.CY Pub Date : 2020-09-21
    Iva Bojic; Dániel Kondor; Wei Tu; Ke Mai; Paolo Santi; Carlo Ratti

    In this paper, we explore existing synergies between private and public transportation as provided by taxi and bus services on the level of individual trips. While these modes are typically separated for economic reasons, in a future with shared Autonomous Vehicles (AVs) providing cheap and efficient transportation services, such distinctions will blur. Consequently, optimization based on real-time

    更新日期:2020-09-22
  • Network and Station-Level Bike-Sharing System Prediction: A San Francisco Bay Area Case Study
    arXiv.cs.CY Pub Date : 2020-09-20
    Huthaifa I. Ashqar; Mohammed Elhenawy; Hesham A. Rakha; Mohammed Almannaa; Leanna House

    The paper develops models for modeling the availability of bikes in the San Francisco Bay Area Bike Share System applying machine learning at two levels: network and station. Investigating BSSs at the station-level is the full problem that would provide policymakers, planners, and operators with the needed level of details to make important choices and conclusions. We used Random Forest and Least-Squares

    更新日期:2020-09-22
  • UniNet: Next Term Course Recommendation using Deep Learning
    arXiv.cs.CY Pub Date : 2020-09-20
    Nicolas Araque; Germano Rojas; Maria Vitali

    Course enrollment recommendation is a relevant task that helps university students decide what is the best combination of courses to enroll in the next term. In particular, recommender system techniques like matrix factorization and collaborative filtering have been developed to try to solve this problem. As these techniques fail to represent the time-dependent nature of academic performance datasets

    更新日期:2020-09-22
  • Software Engineering Standards for Epidemiological Modeling
    arXiv.cs.CY Pub Date : 2020-09-19
    Jack K. Horner; John F. Symons

    There are many normative and technical questions involved in evaluating the quality of software used in epidemiological simulations. In this paper we answer some of these questions and offer practical guidance to practitioners, funders, scientific journals, and consumers of epidemiological research. The heart of our paper is a case study of the Imperial College London (ICL) COVID-19 simulator. We contend

    更新日期:2020-09-22
  • Misinformation and its stakeholders in Europe: a web-based analysis
    arXiv.cs.CY Pub Date : 2020-09-19
    Emmanouil Koulas; Marios Anthopoulos; Sotiria Grammenou; Christos Kaimakamis; Konstantinos Kousaris; Fotini-Rafailia Panavou; Orestis Piskioulis; Syed Iftikhar H. Shah; Vasilios Peristeras

    The rise of the internet and computational power in recent years allowed for the exponential growth of misinformation phenomena. An issue that was a non-issue a decade ago, became a challenge for societal cohesion. The emergence of this new threat has led many stakeholders, especially in Europe, to act in order to tackle this phenomenon. This paper provides in its first part a literature review on

    更新日期:2020-09-22
  • Amazon Fake Reviews
    arXiv.cs.CY Pub Date : 2020-09-18
    Seung Ah Choi

    Often, there are suspicious Amazon reviews that seem to be excessively positive or have been created through a repeating algorithm. I moved to detect fake reviews on Amazon through semantic analysis in conjunction with meta data such as time, word choice, and the user who posted. I first came up with several instances that may indicate a review isn't genuine and constructed what the algorithm would

    更新日期:2020-09-22
  • An AI based talent acquisition and benchmarking for job
    arXiv.cs.CY Pub Date : 2020-08-12
    Rudresh Mishra; Ricardo Rodriguez; Valentin Portillo

    In a recruitment industry, selecting a best CV from a particular job post within a pile of thousand CV's is quite challenging. Finding a perfect candidate for an organization who can be fit to work within organizational culture is a difficult task. In order to help the recruiters to fill these gaps we leverage the help of AI. We propose a methodology to solve these problems by matching the skill graph

    更新日期:2020-09-22
  • Focused Clinical Query Understanding and Retrieval of Medical Snippets powered through a Healthcare Knowledge Graph
    arXiv.cs.CY Pub Date : 2020-09-17
    Maulik R. Kamdar; Michael Carroll; Will Dowling; Linda Wogulis; Cailey Fitzgerald; Matt Corkum; Danielle Walsh; David Conrad; Craig E. Stanley, Jr.; Steve Ross; Dru Henke; Mevan Samarasinghe

    Clinicians face several significant barriers to search and synthesize accurate, succinct, updated, and trustworthy medical information from several literature sources during the practice of medicine and patient care. In this talk, we will be presenting our research behind the development of a Focused Clinical Search Service, powered by a Healthcare Knowledge Graph, to interpret the query intent behind

    更新日期:2020-09-22
  • Feature Selection on Lyme Disease Patient Survey Data
    arXiv.cs.CY Pub Date : 2020-08-24
    Joshua Vendrow; Jamie Haddock; Deanna Needell; Lorraine Johnson

    Lyme disease is a rapidly growing illness that remains poorly understood within the medical community. Critical questions about when and why patients respond to treatment or stay ill, what kinds of treatments are effective, and even how to properly diagnose the disease remain largely unanswered. We investigate these questions by applying machine learning techniques to a large scale Lyme disease patient

    更新日期:2020-09-22
  • What is an intelligent system?
    arXiv.cs.CY Pub Date : 2020-08-31
    Martin Molina

    The concept of intelligent system has emerged in information technology as a type of system derived from successful applications of artificial intelligence. The goal of this paper is to give a general description of an intelligent system, which integrates previous approaches and takes into account recent advances in artificial intelligence. The paper describes an intelligent system in a generic way

    更新日期:2020-09-22
  • Intimate Partner Violence and Injury Prediction From Radiology Reports
    arXiv.cs.CY Pub Date : 2020-08-28
    Irene Y. Chen; Emily Alsentzer; Hyesun Park; Richard Thomas; Babina Gosangi; Rahul Gujrathi; Bharti Khurana

    Intimate partner violence (IPV) is an urgent, prevalent, and under-detected public health issue. We present machine learning models to assess patients for IPV and injury. We train the predictive algorithms on radiology reports with 1) IPV labels based on entry to a violence prevention program and 2) injury labels provided by emergency radiology fellowship-trained physicians. Our full dataset includes

    更新日期:2020-09-22
  • Visilant: Visual Support for the Exploration and Analytical Process Tracking in Criminal Investigations
    arXiv.cs.CY Pub Date : 2020-09-21
    Kristína Zákopčanová; Marko Řeháček; Jozef Bátrna; Daniel Plakinger; Sergej Stoppel; Barbora Kozlíková

    The daily routine of criminal investigators consists of a thorough analysis of highly complex and heterogeneous data of crime cases. Such data can consist of case descriptions, testimonies, criminal networks, spatial and temporal information, and virtually any other data that is relevant for the case. Criminal investigators work under heavy time pressure to analyze the data for relationships, propose

    更新日期:2020-09-22
  • Modelling risk-taking behaviour of avalanche accident victims
    arXiv.cs.CY Pub Date : 2020-09-01
    Robin Couret; Carole Adam; Martial Mermillod

    Each year, over 15000 requests for mountain rescue are counted in France. Avalanche accidents represent 39\% of reports, and are therefore our focus in this study. Modelling the behaviour of mountain accident victims is useful to develop more accurate rescue and prevention tools. Concretely, we observe the interference of two heuristics (availability and familiarity) in decision making when choosing

    更新日期:2020-09-22
  • Beyond Social Media Analytics: Understanding Human Behaviour and Deep Emotion using Self Structuring Incremental Machine Learning
    arXiv.cs.CY Pub Date : 2020-09-05
    Tharindu Bandaragoda

    This thesis develops a conceptual framework considering social data as representing the surface layer of a hierarchy of human social behaviours, needs and cognition which is employed to transform social data into representations that preserve social behaviours and their causalities. Based on this framework two platforms were built to capture insights from fast-paced and slow-paced social data. For

    更新日期:2020-09-22
  • Problems in AI research and how the SP System may help to solve them
    arXiv.cs.CY Pub Date : 2020-09-02
    J Gerard Wolff

    This paper describes problems in AI research and how the SP System may help to solve them. Most of the problems are described by leading researchers in AI in interviews with science writer Martin Ford, and reported by him in his book Architects of Intelligence. These problems, each with potential solutions via SP, are: how to overcome the divide between symbolic and non-symbolic kinds of knowledge

    更新日期:2020-09-22
  • A Survey on Smart Metering Systems using Blockchain for E-Mobility
    arXiv.cs.CY Pub Date : 2020-09-06
    Juan C. Olivares-Rojas; Enrique Reyes-Archundia; José A. Gutiérrez-Gnecchi; Ismael Molina-Moreno

    Electricity is an essential comfort to support our daily activities. With the competitive increase and energy costs by the industry, new values and opportunities for delivering electricity to customers are produced. One of these new opportunities is electric vehicles. With the arrival of electric vehicles, various challenges and opportunities are being presented in the electric power system worldwide

    更新日期:2020-09-22
  • The Relationship between Deteriorating Mental Health Conditions and Longitudinal Behavioral Changes in Google and YouTube Usages among College Students in the United States during COVID-19: Observational Study
    arXiv.cs.CY Pub Date : 2020-09-05
    Anis Zaman; Boyu Zhang; Ehsan Hoque; Vincent Silenzio; Henry Kautz

    Mental health problems among the global population are worsened during the coronavirus disease (COVID-19). How individuals engage with online platforms such as Google Search and YouTube undergoes drastic shifts due to pandemic and subsequent lockdowns. Such ubiquitous daily behaviors on online platforms have the potential to capture and correlate with clinically alarming deteriorations in mental health

    更新日期:2020-09-22
  • Interpretable Machine Learning Approaches to Prediction of Chronic Homelessness
    arXiv.cs.CY Pub Date : 2020-09-12
    Blake VanBerlo; Matthew A. S. Ross; Jonathan Rivard; Ryan Booker

    We introduce a machine learning approach to predict chronic homelessness from de-identified client shelter records drawn from a commonly used Canadian homelessness management information system. Using a 30-day time step, a dataset for 6521 individuals was generated. Our model, HIFIS-RNN-MLP, incorporates both static and dynamic features of a client's history to forecast chronic homelessness 6 months

    更新日期:2020-09-22
  • Running the COVID-19 marathon: the behavioral adaptations in mobility and facemask over 27 weeks of pandemic in Seoul, South Korea
    arXiv.cs.CY Pub Date : 2020-09-09
    Jungwoo Cho; Yuyol Shin; Seyun Kim; Namwoo Kim; Soohwan Oh; Haechan Cho; Yoonjin Yoon

    Battle with COVID-19 turned out to be a marathon, not a sprint, and behavioral adjustments have been unavoidable to stay viable. In this paper, we employ a data-centric approach to investigate individual mobility adaptations and mask-wearing in Seoul, South Korea. We first identify six epidemic phases and two waves based on COVID-19 case count and its geospatial dispersion. The phase-specific linear

    更新日期:2020-09-22
  • Is there a role for statistics in artificial intelligence?
    arXiv.cs.CY Pub Date : 2020-09-13
    Sarah Friedrich; Gerd Antes; Sigrid Behr; Harald Binder; Werner Brannath; Florian Dumpert; Katja Ickstadt; Hans Kestler; Johannes Lederer; Heinz Leitgöb; Markus Pauly; Ansgar Steland; Adalbert Wilhelm; Tim Friede

    The research on and application of artificial intelligence (AI) has triggered a comprehensive scientific, economic, social and political discussion. Here we argue that statistics, as an interdisciplinary scientific field, plays a substantial role both for the theoretical and practical understanding of AI and for its future development. Statistics might even be considered a core element of AI. With

    更新日期:2020-09-22
  • Measurement in AI Policy: Opportunities and Challenges
    arXiv.cs.CY Pub Date : 2020-09-10
    Saurabh Mishra; Jack Clark; C. Raymond Perrault

    As artificial intelligence increasingly influences our world, it becomes crucial to assess its technical progress and societal impact. This paper surveys problems and opportunities in the measurement of AI systems and their impact, based on a workshop held at Stanford University in the fall of 2019. We identify six summary challenges inherent to measuring the progress and impact of AI, and summarize

    更新日期:2020-09-22
  • Hacking with God: a Common Programming Language of Robopsychology and Robophilosophy
    arXiv.cs.CY Pub Date : 2020-09-16
    Norbert Bátfai

    This note is a sketch of how the concept of robopsychology and robophilosophy could be reinterpreted and repositioned in the spirit of the original vocation of psychology and philosophy. The notion of the robopsychology as a fictional science and a fictional occupation was introduced by Asimov in the middle of the last century. The robophilosophy, on the other hand, is only a few years old today. But

    更新日期:2020-09-22
  • A Machine Learning Approach to Detect Suicidal Ideation in US Veterans Based on Acoustic and Linguistic Features of Speech
    arXiv.cs.CY Pub Date : 2020-09-14
    Vaibhav Sourirajan; Anas Belouali; Mary Ann Dutton; Matthew Reinhard; Jyotishman Pathak

    Preventing Veteran suicide is a national priority. The US Department of Veterans Affairs (VA) collects, analyzes, and publishes data to inform suicide prevention strategies. Current approaches for detecting suicidal ideation mostly rely on patient self report which are inadequate and time consuming. In this research study, our goal was to automate suicidal ideation detection from acoustic and linguistic

    更新日期:2020-09-22
  • A Distributed Framework to Orchestrate Video Analytics Applications
    arXiv.cs.CY Pub Date : 2020-09-17
    Tapan Pathak; Vatsal Patel; Sarth Kanani; Shailesh Arya; Pankesh Patel; Muhammad Intizar Ali; John Breslin

    The concept of the Internet of Things (IoT) is a reality now. This paradigm shift has caught everyones attention in a large class of applications, including IoT-based video analytics using smart doorbells. Due to its growing application segments, various efforts exist in scientific literature and many video-based doorbell solutions are commercially available in the market. However, contemporary offerings

    更新日期:2020-09-22
  • Computational appraisal of gender representativeness in popular movies
    arXiv.cs.CY Pub Date : 2020-09-16
    Antoine Mazieres; Telmo Menezes; Camille Roth

    Gender representation in mass media has long been studied by qualitatively analyzing content. This article illustrates how automated computational methods may be used in this context to scale up such empirical observations and increase their resolution and significance. We specifically apply a face and gender detection algorithm on a broad set of popular movies spanning more than three decades to carry

    更新日期:2020-09-22
  • Vehicle Class, Speed, and Roadway Geometry Based Driver Behavior Identification and Classification
    arXiv.cs.CY Pub Date : 2020-09-16
    Awad Abdelhalim; Montasir Abbas

    Over the past decades, the intense emphasis has been placed on the understanding of car-following behavior and the factors that affect it. The car-following process, however, still remains a very complex field of study in spite of all the efforts. This paper focuses on the study of the effect that the class of the vehicle, leading heavy vehicles in particular, causes on the following vehicle behavior

    更新日期:2020-09-22
  • AI-Driven Interface Design for Intelligent Tutoring System Improves Student Engagement
    arXiv.cs.CY Pub Date : 2020-09-18
    Byungsoo Kim; Hongseok Suh; Jaewe Heo; Youngduck Choi

    An Intelligent Tutoring System (ITS) has been shown to improve students' learning outcomes by providing a personalized curriculum that addresses individual needs of every student. However, despite the effectiveness and efficiency that ITS brings to students' learning process, most of the studies in ITS research have conducted less effort to design the interface of ITS that promotes students' interest

    更新日期:2020-09-22
  • Prune Responsibly
    arXiv.cs.CY Pub Date : 2020-09-10
    Michela Paganini

    Irrespective of the specific definition of fairness in a machine learning application, pruning the underlying model affects it. We investigate and document the emergence and exacerbation of undesirable per-class performance imbalances, across tasks and architectures, for almost one million categories considered across over 100K image classification models that undergo a pruning process.We demonstrate

    更新日期:2020-09-22
  • Weakly Supervised Learning of Nuanced Frames for Analyzing Polarization in News Media
    arXiv.cs.CY Pub Date : 2020-09-21
    Shamik Roy; Dan Goldwasser

    In this paper we suggest a minimally-supervised approach for identifying nuanced frames in news article coverage of politically divisive topics. We suggest to break the broad policy frames suggested by Boydstun et al., 2014 into fine-grained subframes which can capture differences in political ideology in a better way. We evaluate the suggested subframes and their embedding, learned using minimal supervision

    更新日期:2020-09-22
  • Exploring the Linear Subspace Hypothesis in Gender Bias Mitigation
    arXiv.cs.CY Pub Date : 2020-09-20
    Francisco Vargas; Ryan Cotterell

    Bolukbasi et al. (2016) presents one of the first gender bias mitigation techniques for word embeddings. Their method takes pre-trained word embeddings as input and attempts to isolate a linear subspace that captures most of the gender bias in the embeddings. As judged by an analogical evaluation task, their method virtually eliminates gender bias in the embeddings. However, an implicit and untested

    更新日期:2020-09-22
  • A framework for effective corporate communication after cyber security incidents
    arXiv.cs.CY Pub Date : 2020-09-19
    Richard Knight; Jason R. C. Nurse

    A major cyber security incident can represent a cyber crisis for an organisation, in particular because of the associated risk of substantial reputational damage. As the likelihood of falling victim to a cyberattack has increased over time, so too has the need to understand exactly what is effective corporate communication after an attack, and how best to engage the concerns of customers, partners

    更新日期:2020-09-22
  • Examining the Impact of Algorithm Awareness on Wikidata's Recommender System Recoin
    arXiv.cs.CY Pub Date : 2020-09-18
    Jesse Josua Benjamin; Claudia Müller-Birn; Simon Razniewski

    The global infrastructure of the Web, designed as an open and transparent system, has a significant impact on our society. However, algorithmic systems of corporate entities that neglect those principles increasingly populated the Web. Typical representatives of these algorithmic systems are recommender systems that influence our society both on a scale of global politics and during mundane shopping

    更新日期:2020-09-22
  • Making Sense of the Robotized Pandemic Response: A Comparison of Global and Canadian Robot Deployments and Success Factors
    arXiv.cs.CY Pub Date : 2020-09-18
    T. BarfootUniversity of Toronto Robotics Institute; J. Burgner-KahrsUniversity of Toronto Robotics Institute; E. DillerUniversity of Toronto Robotics Institute; A. GargUniversity of Toronto Robotics Institute; A. GoldenbergUniversity of Toronto Robotics Institute; J. KellyUniversity of Toronto Robotics Institute; X. LiuUniversity of Toronto Robotics Institute; H. E. NaguibUniversity of Toronto Robotics

    From disinfection and remote triage, to logistics and delivery, countries around the world are making use of robots to address the unique challenges presented by the COVID-19 pandemic. Robots are being used to manage the pandemic in Canada too, but relative to other regions, we have been more cautious in our adoption -- this despite the important role that robots of Canadian origin are now playing

    更新日期:2020-09-21
  • Gateway Controller with Deep Sensing: Learning to be Autonomic in Intelligent Internet of Things
    arXiv.cs.CY Pub Date : 2020-09-18
    Rahim Rahmani; Ramin Firouzi

    The Internet of Things(IoT) will revolutionize the Future Internet through ubiquitous sensing. One of the challenges of having the hundreds of billions of devices that are estimated to be deployed would be rise of an enormous amount of data, along with the devices ability to manage. This paper presents an approach as a controller solution and designed specifically for autonomous management, connectivity

    更新日期:2020-09-21
  • Population Mapping in Informal Settlements with High-Resolution Satellite Imagery and Equitable Ground-Truth
    arXiv.cs.CY Pub Date : 2020-09-17
    Konstantin Klemmer; Godwin Yeboah; João Porto de Albuquerque; Stephen A Jarvis

    We propose a generalizable framework for the population estimation of dense, informal settlements in low-income urban areas--so called 'slums'--using high-resolution satellite imagery. Precise population estimates are a crucial factor for efficient resource allocations by government authorities and NGO's, for instance in medical emergencies. We utilize equitable ground-truth data, which is gathered

    更新日期:2020-09-20
  • Efficient multi-descriptor fusion for non-intrusive appliance recognition
    arXiv.cs.CY Pub Date : 2020-09-17
    Yassine Himeur; Abullah Alsalemi; Faycal Bensaali; Abbes amira

    Consciousness about power consumption at the appliance level can assist user in promoting energy efficiency in households. In this paper, a superior non-intrusive appliance recognition method that can provide particular consumption footprints of each appliance is proposed. Electrical devices are well recognized by the combination of different descriptors via the following steps: (a) investigating the

    更新日期:2020-09-20
  • Building power consumption datasets: Survey, taxonomy and future directions
    arXiv.cs.CY Pub Date : 2020-09-17
    Yassine Himeur; Abdullah Alsalemi; Faycal Bensaali; Abbes Amira

    In the last decade, extended efforts have been poured into energy efficiency. Several energy consumption datasets were henceforth published, with each dataset varying in properties, uses and limitations. For instance, building energy consumption patterns are sourced from several sources, including ambient conditions, user occupancy, weather conditions and consumer preferences. Thus, a proper understanding

    更新日期:2020-09-20
  • Planting trees at the right places: Recommending suitable sites for growing trees using algorithm fusion
    arXiv.cs.CY Pub Date : 2020-09-17
    Pushpendra Rana; Lav R Varshney

    Large-scale planting of trees has been proposed as a low-cost natural solution for carbon mitigation, but is hampered by poor selection of plantation sites, especially in developing countries. To aid in site selection, we develop the ePSA (e-Plantation Site Assistant) recommendation system based on algorithm fusion that combines physics-based/traditional forestry science knowledge with machine learning

    更新日期:2020-09-20
  • Computational models in Electroencephalography
    arXiv.cs.CY Pub Date : 2020-09-17
    Katharina Glomb; Joana Cabral; Anna Cattani; Alberto Mazzoni; Ashish Raj; Benedetta Franceschiello

    Computational models lie at the intersection of basic neuroscience and healthcare applications because they allow researchers to test hypotheses \textit{in silico} and predict the outcome of experiments and interactions that are very hard to test in reality. Yet, what is meant by "computational model" is understood in many different ways by researchers in different fields of neuroscience and psychology

    更新日期:2020-09-20
  • Impact and dynamics of hate and counter speech online
    arXiv.cs.CY Pub Date : 2020-09-16
    Joshua Garland; Keyan Ghazi-Zahedi; Jean-Gabriel Young; Laurent Hébert-Dufresne; Mirta Galesic

    Citizen-generated counter speech is a promising way to fight hate speech and promote peaceful, non-polarized discourse. However, there is a lack of large-scale longitudinal studies of its effectiveness for reducing hate speech. We investigate the effectiveness of counter speech using several different macro- and micro-level measures of over 180,000 political conversations that took place on German

    更新日期:2020-09-20
  • Improving in-home appliance identification using fuzzy-neighbors-preserving analysis based QR-decomposition
    arXiv.cs.CY Pub Date : 2020-09-17
    Yassine Himeur; Abdullah Alsalemi; Faycal Bensaali; Abbes Amira

    This paper proposes a new appliance identification scheme by introducing a novel approach for extracting highly discriminative characteristic sets that can considerably distinguish between various appliance footprints. In this context, a precise and powerful characteristic projection technique depending on fuzzy-neighbors-preserving analysis based QR-decomposition (FNPA-QR) is applied on the extracted

    更新日期:2020-09-20
  • A Linked Aggregate Code for Processing Faces (Revised Version)
    arXiv.cs.CY Pub Date : 2020-09-17
    Michael Lyons; Kazunori Morikawa

    A model of face representation, inspired by the biology of the visual system, is compared to experimental data on the perception of facial similarity. The face representation model uses aggregate primary visual cortex (V1) cell responses topographically linked to a grid covering the face, allowing comparison of shape and texture at corresponding points in two facial images. When a set of relatively

    更新日期:2020-09-20
  • Model-based approach for analyzing prevalence of nuclear cataracts in elderly residents
    arXiv.cs.CY Pub Date : 2020-09-17
    Sachiko Kodera; Akimasa Hirata; Fumiaki Miura; Essam A. Rashed; Natsuko Hatsusaka; Naoki Yamamoto; Eri Kubo; Hiroshi Sasaki

    Recent epidemiological studies have hypothesized that the prevalence of cortical cataracts is closely related to ultraviolet radiation. However, the prevalence of nuclear cataracts is higher in elderly people in tropical areas than in temperate areas. The dominant factors inducing nuclear cataracts have been widely debated. In this study, the temperature increase in the lens due to exposure to ambient

    更新日期:2020-09-20
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