Showing papers in "IEEE Computer in 2019"
IBM1
TL;DR: IBM's brain-inspired processor is a massively parallel neural network inference engine containing 1 million spiking neurons and 256 million low-precision synapses, making it the largest neurosynaptic computer ever built.
Abstract: IBM's brain-inspired processor is a massively parallel neural network inference engine containing 1 million spiking neurons and 256 million low-precision synapses. Now, after a decade of fundamental research spanning neuroscience, architecture, chips, systems, software, and algorithms, IBM has delivered the largest neurosynaptic computer ever built.
137 citations
TL;DR: In this article, the authors present challenges for researchers at the intersection of computer science and the social sciences in online social media, where the exploitation of this lens, termed social sensing, presents challenges.
Abstract: Online social media have democratized the broadcasting of information, encouraging users to view the world through the lens of social networks. The exploitation of this lens, termed social sensing, presents challenges for researchers at the intersection of computer science and the social sciences.
129 citations
TL;DR: The extensive use of these data sets in recent studies to evaluate network intrusion detection systems is a matter of concern and the literature is addressed by addressing these concerns.
Abstract: Many consider the KDD Cup 99 data sets to be outdated and inadequate. Therefore, the extensive use of these data sets in recent studies to evaluate network intrusion detection systems is a matter of concern. We contribute to the literature by addressing these concerns.
85 citations
TL;DR: A digital twin is a digital model of a real entity, the physical twin (such as an object, a process, or a complex aggregation) that is both a digital shadow reflecting the status/operation of its physical twin and a digital thread recording the evolution of the physical twins over time.
Abstract: A digital twin is a digital model of a real entity, the physical twin (such as an object, a process, or a complex aggregation). It is both a digital shadow reflecting the status/operation of its physical twin and a digital thread recording the evolution of the physical twin over time.
78 citations
TL;DR: New developments in the technologies of drone delivery, such as aircraft design, battery improvements, and control software, could transform this industry and, consequently, society as a whole.
Abstract: Despite its enormous economic impact, the parcel delivery industry has evolved slowly over the decades with the biggest innovations coming from GPS and planning algorithms. New developments in the technologies of drone delivery, such as aircraft design, battery improvements, and control software, could transform this industry and, consequently, society as a whole.
61 citations
TL;DR: This work discusses decomposition-based hybrid approaches for solving optimization problems and demonstrates them for applications related to community detection.
Abstract: Solving larger-sized problems is an important area of research in quantum computing. Designing hybrid quantumclassical algorithms is a promising approach to solving this. We discuss decomposition-based hybrid approaches for solving optimization problems and demonstrate them for applications related to community detection.
53 citations
TL;DR: An overview of quantum computers based on the annealing paradigm and manufactured by D-Wave is given and evidence-based predictions about developments in this region of the QC space are presented.
Abstract: An overview of quantum computers based on the annealing paradigm and manufactured by D-Wave is given. An introductory survey of this approach to quantum computing (QC), together with a snapshot of what is known about performance, is presented. Evidence-based predictions about developments in this region of the QC space are presented.
49 citations
TL;DR: It is proposed that a unified mm-wave system for combined communication and robust sensing will turbocharge the capabilities of application domains from in-home digital health to new possibilities for building analytics.
Abstract: Millimeter-wave (mm-wave) technology is emerging as a de facto enabler for next-generation high-rate communications. We propose that a unified mm-wave system for combined communication and robust sensing will turbocharge the capabilities of application domains from in-home digital health to new possibilities for building analytics.
47 citations
TL;DR: This work presents osmotic computing as a new paradigm able to respond to resource heterogeneity, secure data exchange, and efficient microservices deployment across federated cloud systems.
Abstract: Rapid growth and evolution in the number, functionalities, and scope of Internet of Things devices is evident. We present osmotic computing as a new paradigm able to respond to resource heterogeneity, secure data exchange, and efficient microservices deployment across federated cloud systems.
43 citations
TL;DR: The use of emerging blockchain technology to improve Internet of Things-enabled food logistics will help improve integrity and traceability in the distribution and transportation network.
Abstract: Provenance and traceability are crucial in the food distribution and transportation network for ensuring integrity of food labeling and efficient management of quality and contamination issues. Significant issues in terms of cost, quality, and health issues can result without sufficient visibility. This article elaborates on the use of emerging blockchain technology to improve Internet of Things-enabled food logistics.
43 citations
TL;DR: The interdisciplinary nature of sports science introduces challenges such as multifaceted data collection, accuracy in knowledge formation, and equipment usability, which AIoT technology applies to solve.
Abstract: The interdisciplinary nature of sports science introduces challenges such as multifaceted data collection, accuracy in knowledge formation, and equipment usability. Artificial intelligence of things (AIoT) technology presents a feasible solution adaptable to different sports. Taking weight training as an example, we apply AIoT technology to these challenges.
TL;DR: This paper discusses emerging tools, key technology enablers, and distinct deployment experiences with a focus on communications beyond 5G and future industrial applications.
Abstract: With the growing range of radio technologies and sensors used in next-generation industrial plants, radio-frequency sensing systems hold the potential to generate high-value information. We discuss emerging tools, key technology enablers, and distinct deployment experiences with a focus on communications beyond 5G and future industrial applications.
TL;DR: The properties of DLT are reviewed and how two recently developed ideas can be used to retain its advantages while simplifying design are shown.
Abstract: Distributed ledger technology (DLT) offers new and unique advantages for information systems, but some of its features are not a good fit for many applications. We review the properties of DLT and show how two recently developed ideas can be used to retain its advantages while simplifying design.
TL;DR: This work explores the symbiotic relationship between augmented cognition and edge computing, which will require low-latency wireless access to powerful infrastructure resources by lightweight wearable devices to deliver augmented cognition benefits in real time.
Abstract: Augmented cognition can transform human capabilities, but delivering its benefits in real time will require low-latency wireless access to powerful infrastructure resources by lightweight wearable devices. Edge computing is the only viable approach to meeting these stringent requirements. We explore the symbiotic relationship between augmented cognition and edge computing.
TL;DR: Call and messaging logs from mobile devices have successfully been used to predict personality traits, but accelerometer data have not been applied for this purpose.
Abstract: Call and messaging logs from mobile devices have successfully been used to predict personality traits. Yet accelerometer data have not been applied for this purpose. Here we used accelerometer data, along with data from call and messaging logs, to predict five key personality traits.
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Queen's University Belfast1, University of Gothenburg2, University of New Brunswick3, University of Illinois at Chicago4, University of St Andrews5, Lancaster University6, University of Glasgow7, Chung-Ang University8, Loughborough University9, University of Cambridge10, École de technologie supérieure11
TL;DR: A brief history of the cloud and a researcher's view of the prospects for innovating at the infrastructure, middleware, and applications and delivery levels of the already crowded cloud computing stack is presented in this article.
Abstract: The cloud has become integral to most Internet-based applications and user gadgets. This article provides a brief history of the cloud and presents a researcher's view of the prospects for innovating at the infrastructure, middleware, and applications and delivery levels of the already crowded cloud computing stack.
TL;DR: A comprehensive definition of "big data" is provided, various concerns are elaborated, and an initial road map for critical research challenges is articulate.
Abstract: The use of big data combined with powerful machine-learning algorithms raises major concerns over potential adverse effects. Consequently, data transparency is critical for many data-intensive applications. We provide a comprehensive definition, elaborate on various concerns, and articulate an initial road map for critical research challenges.
TL;DR: The challenges in finding better actions to realize Society 5.0 for Sustainable Development Goals through evidence-based policymaking using artificial intelligence are outlined.
Abstract: It is imperative for humans to remain as central actors in the policy- and decisionmaking processes to achieve a sustainable and inclusive society. In this article, we outline the challenges in finding better actions to realize Society 5.0 for Sustainable Development Goals through evidence-based policymaking using artificial intelligence.
TL;DR: This work offers an overview of a framework based on claims, arguments, and evidence aimed at addressing autonomous and machine learning-based systems and uses it to identify specific gaps, challenges, and potential solutions.
Abstract: Autonomous and machine learning-based systems are disruptive innovations and thus require a corresponding disruptive assurance strategy. We offer an overview of a framework based on claims, arguments, and evidence aimed at addressing these systems and use it to identify specific gaps, challenges, and potential solutions.
TL;DR: There are benefits to formalizing translational computer science to complement traditional modes of computer science research, as has been done for translational medicine.
Abstract: There are benefits to formalizing translational computer science (TCS) to complement traditional modes of computer science research, as has been done for translational medicine. TCS has the potential to accelerate the impact of computer science research overall.
TL;DR: An empirical study investigating the user perceptions of a popular dog activity tracker shows that these trackers have a positive impact on owners' motivation to increase their physical activities with their dogs.
Abstract: The pet industry is catching up in the wearables market, and pet activity and location trackers are increasingly worn by our furry friends. We report on an empirical study investigating the user perceptions of a popular dog activity tracker. Results show that these trackers have a positive impact on owners' motivation to increase their physical activities with their dogs.
TL;DR: In this article, a navigational paradigm can help users reach a specific health goal by using constantly captured measurements to estimate how their health is continuously changing and provide actionable guidance, which is similar to our approach.
Abstract: Health and well-being are shaped by how lifestyle and the environment interact with biological machines. A navigational paradigm can help users reach a specific health goal by using constantly captured measurements to estimate how their health is continuously changing and provide actionable guidance.
TL;DR: Advancing the adoption of AI/ML applied to cybersecurity requires partnering of industry, academia, and government on a global scale.
Abstract: Cybersecurity is a key risk for any business as the number of attacks are increasing. Growing attacks on cybersecurity are threatening our existence. Artificial Intelligence (AI) and machine learning (ML) can help detect threats and provide recommendations to cyber analysts. Advancing the adoption of AI/ML applied to cybersecurity requires partnering of industry, academia, and government on a global scale.
TL;DR: A recent survey found that 78% of respondents were concerned about ad fraud and bot traffic, and online advertising frauds cost online advertisers US$19 billion worldwide in 2018.
Abstract: Fraud is a trust issue. Online fraud is a cybertrust issue. Juniper Research estimated that advertising frauds cost online advertisers USd19 billion worldwide in 2018. A recent survey found that 78% of respondents were concerned about ad fraud and bot traffic.
TL;DR: This work evaluated the effectiveness of Cyber Essentials and found that its security controls work well to mitigate threats that exploit vulnerabilities remotely with commodity-level tools.
Abstract: A number of security certifications for small- and medium-size enterprises have been proposed, but how effective are these schemes? We evaluated the effectiveness of Cyber Essentials and found that its security controls work well to mitigate threats that exploit vulnerabilities remotely with commodity-level tools.
TL;DR: A critical examination of existential questions may lead developers to design machines with higher forms of artificial intelligence as discussed by the authors, which would display not merely intelligence but wisdom, inspired by their ability to recognize their own ignorance.
Abstract: A critical examination of existential questions may lead developers to design machines with higher forms of artificial intelligence. Infused by their ability to recognize their own ignorance, these machines would display not merely intelligence but wisdom.
TL;DR: New research and the integration of statistical data-mining methods is required to address data quality, scalability, theoretical grounding, and meaningful presentations.
Abstract: Visual tools that analyze events can reveal patterns, interesting rarities, and troubling anomalies in a vast array of data sets. New research and the integration of statistical data-mining methods is required to address data quality, scalability, theoretical grounding, and meaningful presentations.
TL;DR: This work asks what kinds of risks ML systems pose in terms of security engineering and software security.
Abstract: Artificial intelligence is in the midst of a popular resurgence in the guise of machine learning (ML). Neural networks and deep learning architectures have been shown empirically to solve many real-world problems. We ask what kinds of risks ML systems pose in terms of security engineering and software security.
TL;DR: In this article, the legal status of AI and algorithms continues to be debated, and the authors argue that Resume-sifting algorithms exhibit unethical, discriminatory, and illegal behavior; crime-sentencing algorithms are unable to justify their decisions; and autonomous vehicles' predictive analytics software will make life and death decisions.
Abstract: The legal status of AI and algorithms continues to be debated. Resume-sifting algorithms exhibit unethical, discriminatory, and illegal behavior; crime-sentencing algorithms are unable to justify their decisions; and autonomous vehicles' predictive analytics software will make life and death decisions.
TL;DR: In this paper, the authors discuss how the IEEE Transactions on Computers will closely follow these exciting developments in applying machine learning to computer architectures and provide the latest academic and industry research.
Abstract: Computer architects often face the challenging task of balancing various design considerations, such as performance, power, cost, and reliability. With its unprecedented success in numerous domains and disciplines, machine learning could be a promising approach to solving complicated architecture design and optimization problems. IEEE Transactions on Computers continues to lead research in this area, recently publishing more than 10 papers that propose innovative, viable, and promising ways to take the advantage of machine learning in computer architecture. Discusses how the IEEE Transactions on Computers will closely follow these exciting developments in applying machine learning to computer architectures and provide the latest academic and industry research.