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Eternal Sunshine of the Mechanical Mind: The Irreconcilability of Machine Learning and the Right to be Forgotten arXiv.cs.GL Pub Date : 2024-03-06 Meem Arafat Manab
As we keep rapidly advancing toward an era where artificial intelligence is a constant and normative experience for most of us, we must also be aware of what this vision and this progress entail. By first approximating neural connections and activities in computer circuits and then creating more and more sophisticated versions of this crude approximation, we are now facing an age to come where modern
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A Comprehensive Overview of Fish-Eye Camera Distortion Correction Methods arXiv.cs.GL Pub Date : 2023-12-31 Jian Xu, De-Wei Han, Kang Li, Jun-Jie Li, Zhao-Yuan Ma
The fisheye camera, with its unique wide field of view and other characteristics, has found extensive applications in various fields. However, the fisheye camera suffers from significant distortion compared to pinhole cameras, resulting in distorted images of captured objects. Fish-eye camera distortion is a common issue in digital image processing, requiring effective correction techniques to enhance
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The 4+1 Model of Data Science arXiv.cs.GL Pub Date : 2023-11-13 Rafael C. Alvarado
Data Science is a complex and evolving field, but most agree that it can be defined as a combination of expertise drawn from three broad areascomputer science and technology, math and statistics, and domain knowledge -- with the purpose of extracting knowledge and value from data. Beyond this, the field is often defined as a series of practical activities ranging from the cleaning and wrangling of
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Data Science from 1963 to 2012 arXiv.cs.GL Pub Date : 2023-11-06 Rafael C. Alvarado
Consensus on the definition of data science remains low despite the widespread establishment of academic programs in the field and continued demand for data scientists in industry. Definitions range from rebranded statistics to data-driven science to the science of data to simply the application of machine learning to so-called big data to solve real world problems. Current efforts to trace the history
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Computational Natural Philosophy: A Thread from Presocratics through Turing to ChatGPT arXiv.cs.GL Pub Date : 2023-09-22 Gordana Dodig-Crnkovic
Modern computational natural philosophy conceptualizes the universe in terms of information and computation, establishing a framework for the study of cognition and intelligence. Despite some critiques, this computational perspective has significantly influenced our understanding of the natural world, leading to the development of AI systems like ChatGPT based on deep neural networks. Advancements
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The History of Quantum Games arXiv.cs.GL Pub Date : 2023-09-04 Laura Piispanen, Edward Morrell, Solip Park, Marcell Pfaffhauser, Annakaisa Kultima
In this paper, we explore the historical development of playable quantum physics related games (\textit{\textbf{quantum games}}). For the purpose of this examination, we have collected over 260 quantum games ranging from commercial games, applied and serious games, and games that have been developed at quantum themed game jams and educational courses. We provide an overview of the journey of quantum
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AI empowering research: 10 ways how science can benefit from AI arXiv.cs.GL Pub Date : 2023-07-17 César França
This article explores the transformative impact of artificial intelligence (AI) on scientific research. It highlights ten ways in which AI is revolutionizing the work of scientists, including powerful referencing tools, improved understanding of research problems, enhanced research question generation, optimized research design, stub data generation, data transformation, advanced data analysis, and
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ChatGPT believes it is conscious arXiv.cs.GL Pub Date : 2023-03-29 Arend Hintze
The development of advanced generative chat models, such as ChatGPT, has raised questions about the potential consciousness of these tools and the extent of their general artificial intelligence. ChatGPT consistent avoidance of passing the test is here overcome by asking ChatGPT to apply the Turing test to itself. This explores the possibility of the model recognizing its own sentience. In its own
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The First Computer Program arXiv.cs.GL Pub Date : 2023-03-24 Raúl Rojas
In 1837, the first computer program in history was sketched by the renowned mathematician and inventor Charles Babbage. It was a program for the Analytical Engine. The program consists of a sequence of arithmetical operations and the necessary variable addresses (memory locations) of the arguments and the result, displayed in tabular fashion, like a program trace. The program computes the solutions
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Heckerthoughts arXiv.cs.GL Pub Date : 2023-02-13 David Heckerman
In 1987, Eric Horvitz, Greg Cooper, and I visited I.J. Good at his university. We wanted to see him was not because he worked with Alan Turing to help win WWII by decoding encrypted messages from the Germans, although that certainly intrigued us. Rather, we wanted to see him because we had just finished reading his book "Good Thinking," which summarized his life's work in Probability and its Applications
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Automation and AI Technology in Surface Mining With a Brief Introduction to Open-Pit Operations in the Pilbara arXiv.cs.GL Pub Date : 2023-01-24 Raymond Leung, Andrew J Hill, Arman Melkumyan
This survey article provides a synopsis on some of the engineering problems, technological innovations, robotic development and automation efforts encountered in the mining industry -- particularly in the Pilbara iron-ore region of Western Australia. The goal is to paint the technology landscape and highlight issues relevant to an engineering audience to raise awareness of AI and automation trends
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Charles Babbage, Ada Lovelace, and the Bernoulli Numbers arXiv.cs.GL Pub Date : 2023-01-07 Thomas J. Misa
This chapter makes needed corrections to an unduly negative scholarly view of Ada Lovelace. Credit between Lovelace and Babbage is not a zero-sum game, where any credit added to Lovelace somehow detracts from Babbage. Ample evidence indicates Babbage and Lovelace each had important contributions to the famous 1843 Sketch of Babbage's Analytical Engine and the accompanying Notes. Further, Lovelace's
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Epistemological Equation for Analysing Uncontrollable States in Complex Systems: Quantifying Cyber Risks from the Internet of Things arXiv.cs.GL Pub Date : 2022-12-15 Petar Radanliev, David De Roure, Pete Burnap, Omar Santos
To enable quantitative risk assessment of uncontrollable risk states in complex and coupled IoT systems, a new epistemological equation is designed and tested though comparative and empirical analysis. The comparative analysis is conducted on national digital strategies, followed by an empirical analysis of cyber risk assessment approaches. The new epistemological analysis approach enables the assessment
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Can REF output quality scores be assigned by AI? Experimental evidence arXiv.cs.GL Pub Date : 2022-12-11 Mike Thelwall, Kayvan Kousha, Mahshid Abdoli, Emma Stuart, Meiko Makita, Paul Wilson, Jonathan Levitt
This document describes strategies for using Artificial Intelligence (AI) to predict some journal article scores in future research assessment exercises. Five strategies have been assessed.
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Development of Millimeter Wave Wireless Communication arXiv.cs.GL Pub Date : 2022-11-27 Quanda Zhang, Hudi Wang
The future wireless communication system faces the bottleneck of the shortage of traditional spectrum resources and the explosive growth of the demand for wireless services. Millimeter-wave communication with spectral resources has become an effective choice for the next generation of wireless broadband cellular communication. However, the transmission path loss is large and oxygen and water molecules
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Systematic Literature Review of Gender and Software Engineering in Asia arXiv.cs.GL Pub Date : 2022-11-16 Hironori Washizaki
It is essential to discuss the role, difficulties, and opportunities concerning people of different gender in the field of software engineering research, education, and industry. Although some literature reviews address software engineering and gender, it is still unclear how research and practices in Asia exist for handling gender aspects in software development and engineering. We conducted a systematic
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Digital Literacy and Reading Habits of The DMI-St. Eugene University Students arXiv.cs.GL Pub Date : 2022-10-29 Subaveerapandiyan A, Priyanka Sinha
Digital literacy is the skill of finding, evaluating, consuming, and generating information using digital technologies. The study attempted to comprehend university students' digital reading habits and skills. It also provides a glimpse of the pupils' favorite reading materials, including physical and digital sources. We examined BSc and BE Computer Science students of DMI-St. Eugene University, Zambia
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Cards Against AI: Predicting Humor in a Fill-in-the-blank Party Game arXiv.cs.GL Pub Date : 2022-10-24 Dan Ofer, Dafna Shahaf
Humor is an inherently social phenomenon, with humorous utterances shaped by what is socially and culturally accepted. Understanding humor is an important NLP challenge, with many applications to human-computer interactions. In this work we explore humor in the context of Cards Against Humanity -- a party game where players complete fill-in-the-blank statements using cards that can be offensive or
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Sociotechnical Harms: Scoping a Taxonomy for Harm Reduction arXiv.cs.GL Pub Date : 2022-10-11 Renee Shelby, Shalaleh Rismani, Kathryn Henne, AJung Moon, Negar Rostamzadeh, Paul Nicholas, N'Mah Yilla, Jess Gallegos, Andrew Smart, Emilio Garcia, Gurleen Virk
Understanding the landscape of potential harms from algorithmic systems enables practitioners to better anticipate consequences of the systems they build. It also supports the prospect of incorporating controls to help minimize harms that emerge from the interplay of technologies and social and cultural dynamics. A growing body of scholarship has identified a wide range of harms across different algorithmic
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Software system rationalisation: How to get better outcomes through stronger user engagement arXiv.cs.GL Pub Date : 2022-10-01 Richard Shute, Nick Lynch
As businesses get more sizable and more mature they now, inevitably accrete more and more software systems. This estate expansion leads not only to greater complexity and expense for the enterprise, but also to fragmentation, inconsistency and siloing of business processes. Because platform rationalisation and system decommissioning never happens spontaneously, a perennial problem for the enterprise
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Fast-FNet: Accelerating Transformer Encoder Models via Efficient Fourier Layers arXiv.cs.GL Pub Date : 2022-09-26 Nurullah Sevim, Ege Ozan Özyedek, Furkan Şahinuç, Aykut Koç
Transformer-based language models utilize the attention mechanism for substantial performance improvements in almost all natural language processing (NLP) tasks. Similar attention structures are also extensively studied in several other areas. Although the attention mechanism enhances the model performances significantly, its quadratic complexity prevents efficient processing of long sequences. Recent
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Towards a Standardised Performance Evaluation Protocol for Cooperative MARL arXiv.cs.GL Pub Date : 2022-09-21 Rihab Gorsane, Omayma Mahjoub, Ruan de Kock, Roland Dubb, Siddarth Singh, Arnu Pretorius
Multi-agent reinforcement learning (MARL) has emerged as a useful approach to solving decentralised decision-making problems at scale. Research in the field has been growing steadily with many breakthrough algorithms proposed in recent years. In this work, we take a closer look at this rapid development with a focus on evaluation methodologies employed across a large body of research in cooperative
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Challenges and Opportunities of Large Transnational Datasets: A Case Study on European Administrative Crop Data arXiv.cs.GL Pub Date : 2022-09-19 Maja Schneider, Christian Marchington, Marco Körner
Expansive, informative datasets are vital in providing foundations and possibilities for scientific research and development across many fields of study. Assembly of grand datasets, however, frequently poses difficulty for the author and stakeholders alike, with a variety of considerations required throughout the collaboration efforts and development lifecycle. In this work, we discuss and analyse
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An Overview of Phishing Victimization: Human Factors, Training and the Role of Emotions arXiv.cs.GL Pub Date : 2022-09-13 Mousa Jari
Phishing is a form of cybercrime and a threat that allows criminals, phishers, to deceive end users in order to steal their confidential and sensitive information. Attackers usually attempt to manipulate the psychology and emotions of victims. The increasing threat of phishing has made its study worthwhile and much research has been conducted into the issue. This paper explores the emotional factors
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SIND: A Drone Dataset at Signalized Intersection in China arXiv.cs.GL Pub Date : 2022-09-06 Yanchao Xu, Wenbo Shao, Jun Li, Kai Yang, Weida Wang, Hua Huang, Chen Lv, Hong Wang
Intersection is one of the most challenging scenarios for autonomous driving tasks. Due to the complexity and stochasticity, essential applications (e.g., behavior modeling, motion prediction, safety validation, etc.) at intersections rely heavily on data-driven techniques. Thus, there is an intense demand for trajectory datasets of traffic participants (TPs) in intersections. Currently, most intersections
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Decentralized Infrastructure for (Neuro)science arXiv.cs.GL Pub Date : 2022-09-01 Jonny L. Saunders
The most pressing problems in science are neither empirical nor theoretical, but infrastructural. Scientific practice is defined by coproductive, mutually reinforcing infrastructural deficits and incentive systems that everywhere constrain and contort our art of curiosity in service of profit and prestige. Our infrastructural problems are not unique to science, but reflective of the broader logic of
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Z-Code++: A Pre-trained Language Model Optimized for Abstractive Summarization arXiv.cs.GL Pub Date : 2022-08-21 Pengcheng He, Baolin Peng, Liyang Lu, Song Wang, Jie Mei, Yang Liu, Ruochen Xu, Hany Hassan Awadalla, Yu Shi, Chenguang Zhu, Wayne Xiong, Michael Zeng, Jianfeng Gao, Xuedong Huang
This paper presents Z-Code++, a new pre-trained language model optimized for abstractive text summarization. The model extends the state of the art encoder-decoder model using three techniques. First, we use a two-phase pre-training process to improve model's performance on low-resource summarization tasks. The model is first pre-trained using text corpora for language understanding, and then is continually
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Long-Term Mentoring for Computer Science Researchers arXiv.cs.GL Pub Date : 2022-08-06 Emily Ruppel, Sihang Liu, Elba Garza, Sukyoung Ryu, Alexandra Silva, Talia Ringer
Early in the pandemic, we -- leaders in the research areas of programming languages (PL) and computer architecture (CA) -- realized that we had a problem: the only way to form new lasting connections in the community was to already have lasting connections in the community. Both of our academic communities had wonderful short-term mentoring programs to address this problem, but it was clear that we
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Mary Kenneth Keller: First US PhD in Computer Science arXiv.cs.GL Pub Date : 2022-08-02 Jennifer Head, Dianne P. O'Leary
The first two doctoral-level degrees in Computer Science in the US were awarded in June 1965. This paper discusses one of the degree recipients, Sister Mary Kenneth Keller, BVM.
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RangL: A Reinforcement Learning Competition Platform arXiv.cs.GL Pub Date : 2022-07-28 Viktor Zobernig, Richard A. Saldanha, Jinke He, Erica van der Sar, Jasper van Doorn, Jia-Chen Hua, Lachlan R. Mason, Aleksander Czechowski, Drago Indjic, Tomasz Kosmala, Alessandro Zocca, Sandjai Bhulai, Jorge Montalvo Arvizu, Claude Klöckl, John Moriarty
The RangL project hosted by The Alan Turing Institute aims to encourage the wider uptake of reinforcement learning by supporting competitions relating to real-world dynamic decision problems. This article describes the reusable code repository developed by the RangL team and deployed for the 2022 Pathways to Net Zero Challenge, supported by the UK Net Zero Technology Centre. The winning solutions to
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Towards Specificationless Monitoring of Provenance-Emitting Systems arXiv.cs.GL Pub Date : 2022-07-21 Martin Stoffers, Alexander Weinert
Monitoring often requires insight into the monitored system as well as concrete specifications of expected behavior. More and more systems, however, provide information about their inner procedures by emitting provenance information in a W3C-standardized graph format. In this work, we present an approach to monitor such provenance data for anomalous behavior by performing spectral graph analysis on
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COEM: Cross-Modal Embedding for MetaCell Identification arXiv.cs.GL Pub Date : 2022-07-15 Haiyi Mao, Minxue Jia, Jason Xiaotian Dou Haotian Zhang Panayiotis V. Benos
Metacells are disjoint and homogeneous groups of single-cell profiles, representing discrete and highly granular cell states. Existing metacell algorithms tend to use only one modality to infer metacells, even though single-cell multi-omics datasets profile multiple molecular modalities within the same cell. Here, we present \textbf{C}ross-M\textbf{O}dal \textbf{E}mbedding for \textbf{M}etaCell Identification
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Playing catch-up in building an open research commons arXiv.cs.GL Pub Date : 2022-07-15 Philip E. Bourne, Vivien Bonazzi, Amy Brand, Bonnie Carroll, Ian Foster, Ramanathan V. Guha, Robert Hanisch, Sallie Ann Keller, Mary Lee Kennedy, Christine Kirkpatrick, Barend Mons, Sarah M. Nusser, Michael Stebbins, George Strawn, Alex Szalay
On August 2, 2021 a group of concerned scientists and US funding agency and federal government officials met for an informal discussion to explore the value and need for a well-coordinated US Open Research Commons (ORC); an interoperable collection of data and compute resources within both the public and private sectors which are easy to use and accessible to all.
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Satoshi Nakamoto and the Origins of Bitcoin -- Narratio in Nomine, Datis et Numeris arXiv.cs.GL Pub Date : 2022-06-21 Jens Ducrée
The mystery about the ingenious creator of Bitcoin concealing behind the pseudonym Satoshi Nakamoto has been fascinating the global public for more than a decade. Suddenly jumping out of the dark in 2008, this persona hurled the highly disruptive distributed ledger technology "blockchain" that has added the missing native value layer to the internet. Purposely agnostic without advocating any old or
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Mind the hubris in mathematical modeling arXiv.cs.GL Pub Date : 2022-06-22 Arnald Puy, Andrea Saltelli
Here we briefly reflect on the philosophical foundations that ground the quest towards ever-detailed models and identify four practical dangers derived from this pursuit: explosion of the model's uncertainty space, model black-boxing, computational exhaustion and model attachment. We argue that the growth of a mathematical model should be carefully and continuously pondered lest models become extraneous
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50 Years of Computational Complexity: Hao Wang and the Theory of Computation arXiv.cs.GL Pub Date : 2022-06-12 Nick Zhang
If Turing's groundbreaking paper in 1936 laid the foundation of the theory of computation (ToC), it is no exaggeration to say that Cook's paper in 1971, "The complexity of theorem proving procedures", [4] has pioneered the study of computational complexity. So computational complexity, as an independent research field, is 50 years old now (2021) if we date from Cook's article. This year coincides with
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A Review of Causality for Learning Algorithms in Medical Image Analysis arXiv.cs.GL Pub Date : 2022-06-11 Athanasios Vlontzos, Daniel Rueckert, Bernhard Kainz
Medical image analysis is a vibrant research area that offers doctors and medical practitioners invaluable insight and the ability to accurately diagnose and monitor disease. Machine learning provides an additional boost for this area. However, machine learning for medical image analysis is particularly vulnerable to natural biases like domain shifts that affect algorithmic performance and robustness
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Revisiting Audio Pattern Recognition for Asthma Medication Adherence: Evaluation with the RDA Benchmark Suite arXiv.cs.GL Pub Date : 2022-05-30 Nikos D. Fakotakis, Stavros Nousias, Gerasimos Arvanitis, Evangelia I. Zacharaki, Konstantinos Moustakas
Asthma is a common, usually long-term respiratory disease with negative impact on society and the economy worldwide. Treatment involves using medical devices (inhalers) that distribute medication to the airways, and its efficiency depends on the precision of the inhalation technique. Health monitoring systems equipped with sensors and embedded with sound signal detection enable the recognition of drug
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Moore's Law is dead, long live Moore's Law! arXiv.cs.GL Pub Date : 2022-05-27 Nick Zhang
Moore's Law has been used by semiconductor industry as predicative indicators of the industry and it has become a self-fulfilling prophecy. Now more people tend to agree that the original Moore's Law started to falter. This paper proposes a possible quantitative modification to Moore's Law. It can cover other derivative laws of Moore's Law as well. It intends to more accurately predict the roadmap
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A Survey of Deep Learning Models for Structural Code Understanding arXiv.cs.GL Pub Date : 2022-05-03 Ruoting Wu, Yuxin Zhang, Qibiao Peng, Liang Chen, Zibin Zheng
In recent years, the rise of deep learning and automation requirements in the software industry has elevated Intelligent Software Engineering to new heights. The number of approaches and applications in code understanding is growing, with deep learning techniques being used in many of them to better capture the information in code data. In this survey, we present a comprehensive overview of the structures
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Six Levels of Autonomous Process Execution Management (APEM) arXiv.cs.GL Pub Date : 2022-04-24 Wil van der Aalst
Terms such as the Digital Twin of an Organization (DTO) and Hyperautomation (HA) illustrate the desire to autonomously manage and orchestrate processes, just like we aim for autonomously driving cars. Autonomous driving and Autonomous Process Execution Management (APEM) have in common that the goals are pretty straightforward and that each year progress is made, but fully autonomous driving and fully
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A Brief Guide to Designing and Evaluating Human-Centered Interactive Machine Learning arXiv.cs.GL Pub Date : 2022-04-20 Kory W. Mathewson, Patrick M. Pilarski
Interactive machine learning (IML) is a field of research that explores how to leverage both human and computational abilities in decision making systems. IML represents a collaboration between multiple complementary human and machine intelligent systems working as a team, each with their own unique abilities and limitations. This teamwork might mean that both systems take actions at the same time
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Contextualizing Artificially Intelligent Morality: A Meta-Ethnography of Top-Down, Bottom-Up, and Hybrid Models for Theoretical and Applied Ethics in Artificial Intelligence arXiv.cs.GL Pub Date : 2022-04-15 Jennafer S. Roberts, Laura N. Montoya
In this meta-ethnography, we explore three different angles of Ethical AI design and implementation in a top-down/bottom-up framework, including the philosophical ethical viewpoint, the technical perspective, and framing through a political lens. We will discuss the values and drawbacks of individual and hybrid approaches within this framework. Examples of approaches include ethics either being determined
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The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink arXiv.cs.GL Pub Date : 2022-04-11 David Patterson, Joseph Gonzalez, Urs Hölzle, Quoc Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David So, Maud Texier, Jeff Dean
Machine Learning (ML) workloads have rapidly grown in importance, but raised concerns about their carbon footprint. Four best practices can reduce ML training energy by up to 100x and CO2 emissions up to 1000x. By following best practices, overall ML energy use (across research, development, and production) held steady at <15% of Google's total energy use for the past three years. If the whole ML field
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Advancing Data Justice Research and Practice: An Integrated Literature Review arXiv.cs.GL Pub Date : 2022-04-06 David Leslie, Michael Katell, Mhairi Aitken, Jatinder Singh, Morgan Briggs, Rosamund Powell, Cami Rincón, Thompson Chengeta, Abeba Birhane, Antonella Perini, Smera Jayadeva, Anjali Mazumder
The Advancing Data Justice Research and Practice (ADJRP) project aims to widen the lens of current thinking around data justice and to provide actionable resources that will help policymakers, practitioners, and impacted communities gain a broader understanding of what equitable, freedom-promoting, and rights-sustaining data collection, governance, and use should look like in increasingly dynamic and
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Quantum Computers, Predictability, and Free Will arXiv.cs.GL Pub Date : 2022-04-05 Gil Kalai
This article focuses on the connection between the possibility of quantum computers, the predictability of complex quantum systems in nature, and the issue of free will.
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The EL-X8 computer and the BOL detector Networking, programming, time-sharing and data-handling in the Amsterdam nuclear research project `BOL' A personal historical review arXiv.cs.GL Pub Date : 2022-03-09 René van Dantzig
From 1967 to 1974, an Electrologica X8 computer was installed at the Institute for Nuclear Research (IKO) in Amsterdam, primarily for online and offline evaluation of experimental data, an application quite different from its `brother's', X8's. During that time, the nuclear detection system `BOL' was in operation to study nuclear reactions. The BOL detector embodied a new and bold concept. It consisted
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Emotion Recognition among Couples: A Survey arXiv.cs.GL Pub Date : 2022-02-17 George Boateng, Elgar Fleisch, Tobias Kowatsch
Couples' relationships affect the physical health and emotional well-being of partners. Automatically recognizing each partner's emotions could give a better understanding of their individual emotional well-being, enable interventions and provide clinical benefits. In the paper, we summarize and synthesize works that have focused on developing and evaluating systems to automatically recognize the emotions
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Survey of Big Data sizes in 2021 arXiv.cs.GL Pub Date : 2022-02-15 Luca Clissa
The modern increase in data production is driven by multiple factors, and several stakeholders from various sectors contribute to it. Although drawing a comparison of the sizes at stake for different big data players is hard due to the lack of official data, this report tries to reconstruct the yearly orders of magnitude generated by some of the most important organizations by mining several online
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The Hitchhiker's Guide to Fused Twins -- A Conceptualization to Access Digital Twins in situ in Smart Cities arXiv.cs.GL Pub Date : 2022-02-15 Jascha Grübel
Smart Cities are happening everywhere around us and yet they are still incomprehensibly far from directly impacting everyday life. What needs to happen to make cities really smart? Digital Twins (DTs) represent their Physical Twin (PT) in the real world through models, sensed data, context awareness, and interactions. A Digital Twin of a city appears to offer the right combination to make the Smart
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Data Science in Perspective arXiv.cs.GL Pub Date : 2022-01-15 Rogerio Rossi
Data and Science has stood out in the generation of results, whether in the projects of the scientific domain or business domain. CERN Project, Scientific Institutes, companies like Walmart, Google, Apple, among others, need data to present their results and make predictions in the competitive data world. Data and Science are words that together culminated in a globally recognized term called Data
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A survey study of success factors in data science projects arXiv.cs.GL Pub Date : 2022-01-17 Iñigo Martinez, Elisabeth Viles, Igor G. Olaizola
In recent years, the data science community has pursued excellence and made significant research efforts to develop advanced analytics, focusing on solving technical problems at the expense of organizational and socio-technical challenges. According to previous surveys on the state of data science project management, there is a significant gap between technical and organizational processes. In this
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Data science to investigate temperature profiles of large networks of food refrigeration systems arXiv.cs.GL Pub Date : 2022-01-05 Corneliu Arsene
The electrical generation and transmission infrastructures of many countries are under increased pressure. This partially reflects the move towards low carbon economies and the increased reliance on renewable power generation systems. There has been a reduction in the use of traditional fossil fuel generation systems, which provide a stable base load, and this has been replaced with more unpredictable
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Harmonic numbers as the summation of integrals arXiv.cs.GL Pub Date : 2021-12-01 N. Karjanto
Harmonic numbers arise from the truncation of the harmonic series. The $n^\text{th}$ harmonic number is the sum of the reciprocals of each positive integer up to $n$. In addition to briefly introducing the properties of harmonic numbers, we cover harmonic numbers as the summation of integrals that involve the product of exponential and hyperbolic secant functions. The proof is relatively simple since
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A Taxonomy of Anomalies in Log Data arXiv.cs.GL Pub Date : 2021-11-26 Thorsten Wittkopp, Philipp Wiesner, Dominik Scheinert, Odej Kao
Log data anomaly detection is a core component in the area of artificial intelligence for IT operations. However, the large amount of existing methods makes it hard to choose the right approach for a specific system. A better understanding of different kinds of anomalies, and which algorithms are suitable for detecting them, would support researchers and IT operators. Although a common taxonomy for
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A Review on Analysis and Visualization Methods for Biclustering arXiv.cs.GL Pub Date : 2021-11-23 Melih Sozdinler
Recently, biclustering is one of the hot topics in bioinformatics and takes the attention of authors from several different disciplines. Hence, many different methodologies from a variety of disciplines are proposed as a solution to the biclustering problem. As a consequence of this issue, a variety of solutions makes it harder to evaluate the proposed methods. With this review paper, we are aimed
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Datasets for Online Controlled Experiments arXiv.cs.GL Pub Date : 2021-11-19 C. H. Bryan Liu, Ângelo Cardoso, Paul Couturier, Emma J. McCoy
Online Controlled Experiments (OCE) are the gold standard to measure impact and guide decisions for digital products and services. Despite many methodological advances in this area, the scarcity of public datasets and the lack of a systematic review and categorization hinder its development. We present the first survey and taxonomy for OCE datasets, which highlight the lack of a public dataset to support
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State of the Art of Augmented Reality (AR) Capabilities for Civil Infrastructure Applications arXiv.cs.GL Pub Date : 2021-10-17 Jiaqi Xu, Derek Doyle, Fernando Moreu
Augmented Reality (AR) is a technology superimposing interactional virtual objects onto a real environment. Since the beginning of the millennium, AR technologies have shown rapid growth, with significant research publications in engineering and science. However, the civil infrastructure community has minimally implemented AR technologies to date. One of the challenges that civil engineers face when
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Towards a Theory of Bullshit Visualization arXiv.cs.GL Pub Date : 2021-09-23 Michael Correll
In this unhinged rant, I lay out my suspicion that a lot of visualizations are bullshit: charts that do not have even the common decency to intentionally lie but are totally unconcerned about the state of the world or any practical utility. I suspect that bullshit charts take up a large fraction of the time and attention of actual visualization producers and consumers, and yet are seemingly absent
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Towards the Classification of Error-Related Potentials using Riemannian Geometry arXiv.cs.GL Pub Date : 2021-09-21 Yichen Tang, Jerry J. Zhang, Paul M. Corballis, Luke E. Hallum
The error-related potential (ErrP) is an event-related potential (ERP) evoked by an experimental participant's recognition of an error during task performance. ErrPs, originally described by cognitive psychologists, have been adopted for use in brain-computer interfaces (BCIs) for the detection and correction of errors, and the online refinement of decoding algorithms. Riemannian geometry-based feature