scholarly journals Preparing Society for Automated Vehicles: Perceptions of the Importance and Urgency of Emerging Issues of Governance, Regulations, and Wider Impacts

2020 ◽  
Vol 12 (19) ◽  
pp. 7844 ◽  
Author(s):  
Su-Yen Chen ◽  
Hsin-Yu Kuo ◽  
Chiachun Lee
Keyword(s):  
Autonomous Vehicles ◽  
Data Privacy ◽  
Technology Innovation ◽  
Economic Benefits ◽  
Future Research ◽  
Automated Vehicles ◽  
Innovation Infrastructure ◽  
Emerging Issues ◽  
Different Order ◽  
Urgency Level

This study explores the overall picture of how people perceive the importance level and urgency level regarding issues associated with automated vehicles, by sorting out ten issues, developing a questionnaire with 66 measurement items, and investigating how Artificial Intelligence (AI) experts and Computer Science (CS)/Electrical Engineering (EE) majors assessed these issues. The findings suggest that AI experts in Taiwan believed that the top five issues for preparing a society for autonomous vehicles (AVs) should include (1) data privacy and cybersecurity, (2) regulation considerations, (3) infrastructure, (4) governance, and (5) public acceptance. On the other hand, for their student counterparts, the results (1) demonstrate a somewhat different order from the third to the fifth place, (2) show an attention-focused profile on the issue of cybersecurity and data privacy, and (3) indicate that gender and a few wider-impact variables (technology innovation, infrastructure) are significant predictors for the assessment on the importance level of AVs, while some wider-impact variables (technology innovation, governance, economic benefits, infrastructure), which are positively associated, as well as concerns variables (cybersecurity and data privacy, regulations), which are negatively associated, could be predictors for the urgency level of AVs. Suggestions for future research and policymakers are provided.

scholarly journals Basing Information on Comprehensive, Critically Appraised, and Up-to-Date Syntheses of the Scientific Evidence: An Update from the International Patient Decision Aid Standards

2021 ◽  
pp. 0272989X2199662
Author(s):  
Tammy C. Hoffmann ◽  
Mina Bakhit ◽  
Marie-Anne Durand ◽  
Lilisbeth Perestelo-Pérez ◽  
Catherine Saunders ◽  
...  
Keyword(s):  
Decision Aid ◽  
Scientific Evidence ◽  
Decision Aids ◽  
Future Research ◽  
Patient Decision Aid ◽  
Patient Decision Aids ◽  
Research Areas ◽  
Patient Decision ◽  
Evidence Quality ◽  
Emerging Issues

Background Patients and clinicians expect the information in patient decision aids to be based on the best available research evidence. The objectives of this International Patient Decision Aid Standards (IPDAS) review were to 1) check the currency of, and where needed, update evidence for the domain of “basing the information in decision aids on comprehensive, critically appraised, and up-to-date syntheses of the evidence”; 2) analyze the evidence characteristics of decision aids; and 3) propose updates to relevant IPDAS criteria. Methods We searched MEDLINE and PubMed to inform updates of this domain’s definitions, justifications, and components. We also searched 5 sources to identify all publicly available decision aids ( N = 471). Two assessors independently extracted each aid’s evidence characteristics. Results Minor updates to the definitions and theoretical justifications of this IPDAS domain are provided and changes to relevant IPDAS criteria proposed. Nearly all aids (97%) provided a year of creation/update, but most (81%) did not report an explicit update or expiration policy. No scientific references were cited in 33% of aids. Of the 314 that cited at least 1 reference, 39% cited at least 1 guideline, 44% cited at least 1 systematic review, and 23% cited at least 1 randomized trial. In 35%, it was unclear what statement in the aid the citations referred to. Only 14% reported any of the processes used to find and decide on evidence inclusion. Only 14% reported the evidence quality. Many emerging issues and future research areas were identified. Conclusions Although many emerging issues need to be addressed, this IPDAS domain is validated and criteria refined. High-quality patient decision aids should be based on comprehensive and up-to-date syntheses of critically appraised evidence.

scholarly journals Federated Quantum Machine Learning

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 460
Author(s):  
Samuel Yen-Chi Chen ◽  
Shinjae Yoo
Keyword(s):  
Machine Learning ◽  
Data Privacy ◽  
Research Direction ◽  
Future Research ◽  
Quantum Computers ◽  
Training Time ◽  
Quantum Neural Network ◽  
Distributed Training ◽  
Machine Learning Model ◽  
Quantum Machine Learning

Distributed training across several quantum computers could significantly improve the training time and if we could share the learned model, not the data, it could potentially improve the data privacy as the training would happen where the data is located. One of the potential schemes to achieve this property is the federated learning (FL), which consists of several clients or local nodes learning on their own data and a central node to aggregate the models collected from those local nodes. However, to the best of our knowledge, no work has been done in quantum machine learning (QML) in federation setting yet. In this work, we present the federated training on hybrid quantum-classical machine learning models although our framework could be generalized to pure quantum machine learning model. Specifically, we consider the quantum neural network (QNN) coupled with classical pre-trained convolutional model. Our distributed federated learning scheme demonstrated almost the same level of trained model accuracies and yet significantly faster distributed training. It demonstrates a promising future research direction for scaling and privacy aspects.

First encounter effects in testing of highly automated vehicles during two experimental occasions – The need for recurrent testing

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jonas Andersson ◽  
Azra Habibovic ◽  
Daban Rizgary
Keyword(s):  
Driver Behavior ◽  
Added Value ◽  
Future Research ◽  
Gaze Behavior ◽  
Repeated Testing ◽  
Automated Vehicles ◽  
Automated Driving ◽  
Perceived Safety ◽  
Repeated Interaction ◽  
Over Time

Abstract To explore driver behavior in highly automated vehicles (HAVs), independent researchers are mainly conducting short experiments. This limits the ability to explore drivers’ behavioral changes over time, which is crucial when research has the intention to reveal human behavior beyond the first-time use. The current paper shows the methodological importance of repeated testing in experience and behavior related studies of HAVs. The study combined quantitative and qualitative data to capture effects of repeated interaction between drivers and HAVs. Each driver ( n = 8 n=8 ) participated in the experiment on two different occasions (∼90 minutes) with one-week interval. On both occasions, the drivers traveled approximately 40 km on a rural road at AstaZero proving grounds in Sweden and encountered various traffic situations. The participants could use automated driving (SAE level 4) or choose to drive manually. Examples of data collected include gaze behavior, perceived safety, as well as interviews and questionnaires capturing general impressions, trust and acceptance. The analysis shows that habituation effects were attenuated over time. The drivers went from being exhilarated on the first occasion, to a more neutral behavior on the second occasion. Furthermore, there were smaller variations in drivers’ self-assessed perceived safety on the second occasion, and drivers were faster to engage in non-driving related activities and become relaxed (e. g., they spent more time glancing off road and could focus more on non-driving related activities such as reading). These findings suggest that exposing drivers to HAVs on two (or more) successive occasions may provide more informative and realistic insights into driver behavior and experience as compared to only one occasion. Repeating an experiment on several occasions is of course a balance between the cost and added value, and future research should investigate in more detail which studies need to be repeated on several occasions and to what extent.

scholarly journals Rethinking SME default prediction: a systematic literature review and future perspectives

2021 ◽  
Author(s):  
Francesco Ciampi ◽  
Alessandro Giannozzi ◽  
Giacomo Marzi ◽  
Edward I. Altman
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Global Financial Crisis ◽  
Analytical Techniques ◽  
Future Research ◽  
Finance Management ◽  
Default Prediction ◽  
Emerging Issues ◽  
Medium Enterprise ◽  
Modern Analytical

AbstractOver the last dozen years, the topic of small and medium enterprise (SME) default prediction has developed into a relevant research domain that has grown for important reasons exponentially across multiple disciplines, including finance, management, accounting, and statistics. Motivated by the enormous toll on SMEs caused by the 2007–2009 global financial crisis as well as the recent COVID-19 crisis and the consequent need to develop new SME default predictors, this paper provides a systematic literature review, based on a statistical, bibliometric analysis, of over 100 peer-reviewed articles published on SME default prediction modelling over a 34-year period, 1986 to 2019. We identified, analysed and reviewed five streams of research and suggest a set of future research avenues to help scholars and practitioners address the new challenges and emerging issues in a changing economic environment. The research agenda proposes some new innovative approaches to capture and exploit new data sources using modern analytical techniques, like artificial intelligence, machine learning, and macro-data inputs, with the aim of providing enhanced predictive results.

scholarly journals A Comprehensive Survey on Local Differential Privacy

2020 ◽  
Vol 2020 ◽  
pp. 1-29 ◽  
Author(s):  
Xingxing Xiong ◽  
Shubo Liu ◽  
Dan Li ◽  
Zhaohui Cai ◽  
Xiaoguang Niu
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Statistical Learning ◽  
Data Privacy ◽  
Statistical Estimation ◽  
Differential Privacy ◽  
Future Research ◽  
Reference Source ◽  
Complex Data ◽  
Comprehensive Survey

With the advent of the era of big data, privacy issues have been becoming a hot topic in public. Local differential privacy (LDP) is a state-of-the-art privacy preservation technique that allows to perform big data analysis (e.g., statistical estimation, statistical learning, and data mining) while guaranteeing each individual participant’s privacy. In this paper, we present a comprehensive survey of LDP. We first give an overview on the fundamental knowledge of LDP and its frameworks. We then introduce the mainstream privatization mechanisms and methods in detail from the perspective of frequency oracle and give insights into recent studied on private basic statistical estimation (e.g., frequency estimation and mean estimation) and complex statistical estimation (e.g., multivariate distribution estimation and private estimation over complex data) under LDP. Furthermore, we present current research circumstances on LDP including the private statistical learning/inferencing, private statistical data analysis, privacy amplification techniques for LDP, and some application fields under LDP. Finally, we identify future research directions and open challenges for LDP. This survey can serve as a good reference source for the research of LDP to deal with various privacy-related scenarios to be encountered in practice.

The potential environmental risks associated with the development of rare earth element production in Canada

2021 ◽  
Author(s):  
XIANGBO YIN ◽  
Christine Martineau ◽  
Isabelle Demers ◽  
Nathan Basiliko ◽  
Nicole J. Fenton
Keyword(s):  
Rare Earth ◽  
Rare Earth Element ◽  
Earth Element ◽  
Permanent Magnets ◽  
Indigenous Communities ◽  
Economic Benefits ◽  
Environmental Risks ◽  
Future Research ◽  
Ecological Health ◽  
Climate Conditions

The development of rare earth element (REE) production in Canada could generate significant economic benefits, but also poses serious potential risks to the environment. Rare earth elements have been widely used in modern life and industries, and even are indispensable in some crucial advanced technologies (e.g. permanent magnets). Increasing demand and the context of current US-China trade tensions provide a commercial economic development opportunity for Canada, which has rich resources of REEs, to develop its own sector. However, environmental and health issues caused by REE production are challenges Canada has to face, given that significant environmental impacts have been reported elsewhere (e.g. China). Little literature is available on the potential environmental risks associated with the development of REE production in Canada. It is important to know what environmental issues, particularly those generated by REEs themselves, may happen in Canada in the future. Therefore, three major aspects are evaluated and summarized from multidisciplinary perspectives in this paper: 1) a general conceptual model of the transport of REEs as a group in the environment is established; 2) toxicity levels, biochemical mechanisms, and physiological effects of REEs on different organisms are reviewed, and case-studies from existing REE mining areas are briefly highlighted; and 3) considering specific environmental condition and risk factors, environmental risks Canada may face in future REE developments are identified and discussed. This review concludes with a macro-identification of potential environmental risks associated with the development of REE production in Canada considering both human and ecological health. We note that ingestion, inhalation and dermal exposure for workers and surrounding residents (including potentially indigenous communities), and sub-arctic/arctic climate conditions could increase the risks to human and ecological health in future REE production development in Canada. Finally, future research directions are proposed that could be applied to both Canadian and other geographical contexts.

scholarly journals The formation, properties and impact of secondary organic aerosol: current and emerging issues

2009 ◽  
Vol 9 (14) ◽  
pp. 5155-5236 ◽  
Author(s):  
M. Hallquist ◽  
J. C. Wenger ◽  
U. Baltensperger ◽  
Y. Rudich ◽  
D. Simpson ◽  
...  
Keyword(s):  
Secondary Organic Aerosol ◽  
Analytical Techniques ◽  
Organic Aerosol ◽  
Future Research ◽  
Detailed Knowledge ◽  
Aerosol Formation ◽  
Organic Components ◽  
Modeling Studies ◽  
Tropospheric Aerosol ◽  
Emerging Issues

Abstract. Secondary organic aerosol (SOA) accounts for a significant fraction of ambient tropospheric aerosol and a detailed knowledge of the formation, properties and transformation of SOA is therefore required to evaluate its impact on atmospheric processes, climate and human health. The chemical and physical processes associated with SOA formation are complex and varied, and, despite considerable progress in recent years, a quantitative and predictive understanding of SOA formation does not exist and therefore represents a major research challenge in atmospheric science. This review begins with an update on the current state of knowledge on the global SOA budget and is followed by an overview of the atmospheric degradation mechanisms for SOA precursors, gas-particle partitioning theory and the analytical techniques used to determine the chemical composition of SOA. A survey of recent laboratory, field and modeling studies is also presented. The following topical and emerging issues are highlighted and discussed in detail: molecular characterization of biogenic SOA constituents, condensed phase reactions and oligomerization, the interaction of atmospheric organic components with sulfuric acid, the chemical and photochemical processing of organics in the atmospheric aqueous phase, aerosol formation from real plant emissions, interaction of atmospheric organic components with water, thermodynamics and mixtures in atmospheric models. Finally, the major challenges ahead in laboratory, field and modeling studies of SOA are discussed and recommendations for future research directions are proposed.

scholarly journals A Review of Sensing and Communication, Human Factors, and Controller Aspects for Information-Aware Connected and Automated Vehicles

2020 ◽  
Author(s):  
Mizanur Rahman ◽  
Ankur Sarker ◽  
Haiying Shen ◽  
Mashrur Chowdhury ◽  
Kakan Dey ◽  
...  
Keyword(s):  
Human Factors ◽  
Controller Design ◽  
Route Planning ◽  
Communication Technologies ◽  
Future Research ◽  
Automated Vehicles ◽  
Driving Mode ◽  
Roadway Safety ◽  
Driving Model ◽  
Future Research Directions

Information-aware connected and automated vehicles (CAVs) have drawn great attention in recent years due to their potentially significant positive impacts on roadway safety and operational efficiency. In this paper, we conduct an in-depth review of three basic and key interrelated aspects of a CAV: sensing and communication technologies; human factors; and information-aware controller design. First, the different vehicular sensing and communication technologies and their protocol stacks, to provide reliable information to the information-aware CAV controller, are thoroughly discussed. Diverse human factors, such as user comfort, preferences, and reliability, to design the CAV systems for mass adaptation are also discussed. Then, the different layers of a CAV controller (route planning, driving mode execution, and driving model selection) considering human factors and information through connectivity are reviewed. In addition, the critical challenges for the sensing and communication technologies, human factors, and information-aware controller are identified to support the design of a safe and efficient CAV system while considering user acceptance and comfort. Finally, the promising future research directions of these three aspects are discussed to overcome existing challenges to realize a safe and operationally efficient CAV.

scholarly journals What's Steering Consumer Preferences For Autonomous Vehicles In The Greater Toronto And Hamilton Area?

2021 ◽  
Author(s):  
Kailey Laidlaw
Keyword(s):  
Willingness To Pay ◽  
Household Income ◽  
Autonomous Vehicles ◽  
Consumer Preferences ◽  
Demographic Characteristics ◽  
Social Goals ◽  
Automated Vehicles ◽  
Car Accidents ◽  
Frequency Of Use ◽  
Environment Variables

Automated vehicles (AVs) have the potential to change the way we travel within our cities. However, the conditions under which consumers will adopt AVs are poorly understood. An internet-based survey was conducted in the Greater Toronto and Hamilton Area to understand how consumers will respond to automated vehicles. This study estimates the effect of demographic characteristics, travel characteristics, and built-environment variables on respondent’s willingness to pay for private autonomous vehicles and frequency of use for shared autonomous vehicles under different pricing levels. The results indicate that having a higher household income and owning a more expensive vehicle are good predictors of interest in PAVs, whereas individuals who experienced more car accidents as a passenger and individuals who commute using public transit or walk/cycle are more interested in SAVs. Regional rail users, Uber users, and younger respondents were interested in both ownership models. This provides insight to help policymakers advance transportation policies and collective social goals.

scholarly journals Carpooling in Connected and Autonomous Vehicles: Current Solutions and Future Directions

2022 ◽  
Author(s):  
Farkhanda Zafar ◽  
Hasan Ali Khattak ◽  
Moayad Aloqaily ◽  
Rasheed Hussain
Keyword(s):  
Business Model ◽  
Autonomous Vehicles ◽  
Research Work ◽  
Relevant Information ◽  
Security And Privacy ◽  
Future Research ◽  
Research Directions ◽  
Comprehensive Survey ◽  
One Stop ◽  
Future Research Directions

Owing to the advancements in communication and computation technologies, the dream of commercialized connected and autonomous cars is becoming a reality. However, among other challenges such as environmental pollution, cost, maintenance, security, and privacy, the ownership of vehicles (especially for Autonomous Vehicles (AV)) is the major obstacle in the realization of this technology at the commercial level. Furthermore, the business model of pay-as-you-go type services further attracts the consumer because there is no need for upfront investment. In this vein, the idea of car-sharing ( aka carpooling) is getting ground due to, at least in part, its simplicity, cost-effectiveness, and affordable choice of transportation. Carpooling systems are still in their infancy and face challenges such as scheduling, matching passengers interests, business model, security, privacy, and communication. To date, a plethora of research work has already been done covering different aspects of carpooling services (ranging from applications to communication and technologies); however, there is still a lack of a holistic, comprehensive survey that can be a one-stop-shop for the researchers in this area to, i) find all the relevant information, and ii) identify the future research directions. To fill these research challenges, this paper provides a comprehensive survey on carpooling in autonomous and connected vehicles and covers architecture, components, and solutions, including scheduling, matching, mobility, pricing models of carpooling. We also discuss the current challenges in carpooling and identify future research directions. This survey is aimed to spur further discussion among the research community for the effective realization of carpooling.

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